Unlock 30% off on Manual Testing Annual Plans this Holiday Season.

Copied to Clipboard!

How to use getlist method in tox

Best Python code snippet using tox_python

app.py

Source:app.py

...6162@app.route('/index', methods=['GET', 'POST'])63def index():64    if request.method == 'POST':65        print(request.form.getlist('hello'))66        z = request.form.getlist('hello')67        if z[0] == '1':68            return redirect(url_for('svc'))69        if z[0] == '2':70            return redirect(url_for('knn'))71        if z[0] == '3':72            return redirect(url_for('logistic'))73        if z[0] == '4':74            return redirect(url_for('adaboost'))75        if z[0] == '5':76            return redirect(url_for('naive'))77        if z[0] == '6':78            return redirect(url_for('resnet18'))79        if z[0] == '7':80            return redirect(url_for('resnet34'))81        if z[0] == '8':82            return redirect(url_for('resnet50'))83        if z[0] == '9':84            return redirect(url_for('resnet101'))85        if z[0] == '10':86            return redirect(url_for('resnet152'))87        if z[0] == '11':88            return redirect(url_for('densenet121'))89        if z[0] == '12':90            return redirect(url_for('densenet169'))91        if z[0] == '13':92            return redirect(url_for('densenet201'))93        if z[0] == '14':94            return redirect(url_for('densenet161'))95        if z[0] == '15':96            return redirect(url_for('alexnet'))97        if z[0] == '16':98            return redirect(url_for('squeezenet1_0'))99        if z[0] == '17':100            return redirect(url_for('squeezenet1_1'))101        if z[0] == '18':102            return redirect(url_for('vgg11'))103        if z[0] == '19':104            return redirect(url_for('vgg11_bn'))105        if z[0] == '20':106            return redirect(url_for('vgg13'))107        if z[0] == '21':108            return redirect(url_for('vgg13_bn'))109        if z[0] == '22':110            return redirect(url_for('vgg16'))111        if z[0] == '23':112            return redirect(url_for('vgg16_bn'))113        if z[0] == '24':114            return redirect(url_for('vgg19'))115        if z[0] == '25':116            return redirect(url_for('vgg19_bn'))117    try:118        #global filename119        import os120        num_classes = len(os.listdir(os.path.splitext(filename)[0]))121        print("Number of classes : ",num_classes)122    except:123        num_classes = "error"124    return render_template('select_model.html',filename=filename,num_class=num_classes)125126@app.route('/returnmodel/')127def returnmodel():128	try:129		return send_file("model.pkl")130	except Exception as e:131		return str(e)132133@app.route('/svc_classifier', methods=['GET', 'POST'])134def svc():135    global filename136    if request.method == 'POST':137        print(request.form.getlist('kernal')[0])138        kernel = request.form.getlist('kernal')[0]139        print(request.form.getlist('gamma')[0])140        gamma = request.form.getlist('gamma')[0]141        print(request.form.getlist('decision_function_shape')[0])142        decision_function_shape = request.form.getlist('decision_function_shape')[0]143        print(request.form.getlist('max_iter')[0])144        try:145            max_iter = int(request.form.getlist('max_iter')[0])146        except:147            max_iter = -1148        print(request.form.getlist('random_state')[0])149        try:150            random_state = int(request.form.getlist('random_state')[0])151        except:152            random_state = None153        print(request.form.getlist('shape1')[0])154        shape11 = int(request.form.getlist('shape1')[0])155        print(request.form.getlist('shape2')[0])156        shape22 = int(request.form.getlist('shape2')[0])157        import trainer158        a,bz = trainer.svc_model(kernel1=kernel,gamma1=gamma,max_iter1=max_iter, decision_function_shape1=decision_function_shape,random_state1=random_state,shape1 = shape11,shape2=shape22,file=os.path.splitext(filename)[0])159        global filename2160        filename2 = a161        global b162        b = bz163        return redirect(url_for('svc'))164    return render_template('upload_svc.html',something=str(b))165166@app.route('/logistic_classifier', methods=['GET', 'POST'])167def logistic():168    if request.method == 'POST':169        print(request.form.getlist('criterion'))170        print(request.form.getlist('splitter'))171        print(request.form.getlist('max_depth'))172        print(request.form.getlist('random_state'))173        print(request.form.getlist('min_samples_split'))174        print(request.form.getlist('max_features'))175        print(request.form.getlist('shape1')[0])176        shape11 = int(request.form.getlist('shape1')[0])177        print(request.form.getlist('shape2')[0])178        shape22 = int(request.form.getlist('shape2')[0])179        try:180            max_depth = int(request.form.getlist('max_depth')[0])181        except:182            max_depth = None183        try:184            min_samples_split = int(request.form.getlist('min_samples_split')[0])185        except:186            min_samples_split = 2187        try:188            min_samples_leaf = int(request.form.getlist('min_samples_leaf')[0])189        except:190            min_samples_leaf = 2191        try:192            random_state = int(request.form.getlist('random_state')[0])193        except:194            random_state = None195        if request.form.getlist('max_features')[0] == "None":196            max_features = None197        else:198            max_features = request.form.getlist('max_features')[0]199        criterion = request.form.getlist('criterion')[0]200        splitter = request.form.getlist('splitter')[0]201        global filename202        import trainer203        a,bz = trainer.logistic(criterion1=criterion, splitter1=splitter, max_depth1=max_depth, min_samples_split1=min_samples_split,min_samples_leaf1 =min_samples_leaf ,max_features1=max_features,random_state1=random_state,shape1 = shape11,shape2= shape22,file=os.path.splitext(filename)[0])204        filename2 = a205        global b206        b = bz207        return redirect(url_for('logistic'))208    return render_template('upload_logistic.html',something=str(b))209210@app.route('/adaboost_classifier', methods=['GET', 'POST'])211def adaboost():212    global filename213    if request.method == 'POST':214        print(request.form.getlist('learning_rate'))215        print(request.form.getlist('random_state'))216        print(request.form.getlist('n_estimators'))217        try:218            learning_rate = float(request.form.getlist('learning_rate')[0])219        except:220            learning_rate = 0.1221        try:222            random_state = int(request.form.getlist('random_state')[0])223        except:224            random_state = None225        try:226            n_estimators = int(request.form.getlist('n_estimators')[0])227        except:228            n_estimators = 100229        print(request.form.getlist('shape1')[0])230        shape11 = int(request.form.getlist('shape1')[0])231        print(request.form.getlist('shape2')[0])232        shape22 = int(request.form.getlist('shape2')[0])233        import trainer234        global filename235        a,bz = trainer.adaboost(n_estimators1=n_estimators,random_state1=random_state,learning_rate1=learning_rate,shape1 = shape11,shape2= shape22,file=os.path.splitext(filename)[0])236        global filename2237        filename2 = a238        global b239        b = bz240        return redirect(url_for('adaboost'))241    return render_template('upload_adaboost.html',something=str(b))242243@app.route('/knn_classifier', methods=['GET', 'POST'])244def knn():245    global filename246    if request.method == 'POST':247        print(request.form.getlist('weights'))248        print(request.form.getlist('algorithm'))249        print(request.form.getlist('leaf_size'))250        print(request.form.getlist('n_neighbors'))251        weights = request.form.getlist('weights')[0]252        algorithm = request.form.getlist('algorithm')[0]253        try:254            leaf_size = int(request.form.getlist('leaf_size')[0])255        except:256            leaf_size = 30257        try:258            n_neighbors = int(request.form.getlist('n_neighbors')[0])259        except:260            n_neighbors = 5261        print(request.form.getlist('shape1')[0])262        shape11 = int(request.form.getlist('shape1')[0])263        print(request.form.getlist('shape2')[0])264        shape22 = int(request.form.getlist('shape2')[0])265        import trainer266        a,bz = trainer.knn(weights1 =weights,leaf_size1=leaf_size,n_neighbors1 = n_neighbors,algorithm1 = algorithm,shape1 = shape11,shape2= shape22,file=os.path.splitext(filename)[0])267        global filename2268        filename2 = a269        global b270        b = bz271        return redirect(url_for('knn'))272    return render_template('upload_knn.html',something=str(b))273274@app.route('/naive_classifier', methods=['GET', 'POST'])275def naive():276    if request.method == 'POST':277        print(request.form.getlist('shape1')[0])278        shape11 = int(request.form.getlist('shape1')[0])279        print(request.form.getlist('shape2')[0])280        shape22 = int(request.form.getlist('shape2')[0])281        import trainer282        a,bz = trainer.naivebayes(shape1 = shape11,shape2= shape22,file=os.path.splitext(filename)[0])283        global filename2284        filename2 = a285        global b286        b = bz287        return redirect(url_for('naive'))288    return render_template('upload_naive.html',something=str(b))289290291292@app.route('/resnet18_classifier', methods=['GET', 'POST'])293def resnet18():294    global filename295    if request.method == 'POST':296        print(request.form.getlist('augmentation')[0])297        try:298            augmentation = int(request.form.getlist('augmentation')[0])299        except:300            augmentation = 1301        try:302            epochs = int(request.form.getlist('epochs')[0])303        except:304            epochs = 4305        print(request.form.getlist('epochs')[0])306        print(request.form.getlist('validation_split')[0])307        validation_split = float(request.form.getlist('validation_split')[0])308        import dl_trainer309        file = os.path.splitext(filename)[0]310        a,bz = dl_trainer.dl_models(filename=file,model=1,aug=augmentation,epochs=epochs,validation_split=validation_split)311        global filename2312        filename2 = a313        global b314        b = bz315        return redirect(url_for('resnet18'))316    return render_template('upload_resnet18.html',something=str(b))317318@app.route('/resnet34_classifier', methods=['GET', 'POST'])319def resnet34():320    global filename321    if request.method == 'POST':322        print(request.form.getlist('augmentation')[0])323        try:324            augmentation = int(request.form.getlist('augmentation')[0])325        except:326            augmentation = 1327        try:328            epochs = int(request.form.getlist('epochs')[0])329        except:330            epochs = 4331        print(request.form.getlist('epochs')[0])332        print(request.form.getlist('validation_split')[0])333        validation_split = float(request.form.getlist('validation_split')[0])334        import dl_trainer335        file = os.path.splitext(filename)[0]336        a,bz = dl_trainer.dl_models(filename=file,model=2,aug=augmentation,epochs=epochs,validation_split=validation_split)337        global filename2338        filename2 = a339        global b340        b = bz341        return redirect(url_for('resnet34'))342    return render_template('upload_resnet34.html',something=str(b))343344@app.route('/resnet50_classifier', methods=['GET', 'POST'])345def resnet50():346    global filename347    if request.method == 'POST':348        print(request.form.getlist('augmentation')[0])349        try:350            augmentation = int(request.form.getlist('augmentation')[0])351        except:352            augmentation = 1353        try:354            epochs = int(request.form.getlist('epochs')[0])355        except:356            epochs = 4357        print(request.form.getlist('epochs')[0])358        print(request.form.getlist('validation_split')[0])359        validation_split = float(request.form.getlist('validation_split')[0])360        import dl_trainer361        file = os.path.splitext(filename)[0]362        a,bz = dl_trainer.dl_models(filename=file,model=3,aug=augmentation,epochs=epochs,validation_split=validation_split)363        global filename2364        filename2 = a365        global b366        b = bz367        return redirect(url_for('resnet50'))368    return render_template('upload_resnet50.html',something=str(b))369370@app.route('/resnet101_classifier', methods=['GET', 'POST'])371def resnet101():372    global filename373    if request.method == 'POST':374        print(request.form.getlist('augmentation')[0])375        try:376            augmentation = int(request.form.getlist('augmentation')[0])377        except:378            augmentation = 1379        try:380            epochs = int(request.form.getlist('epochs')[0])381        except:382            epochs = 4383        print(request.form.getlist('epochs')[0])384        print(request.form.getlist('validation_split')[0])385        validation_split = float(request.form.getlist('validation_split')[0])386        import dl_trainer387        file = os.path.splitext(filename)[0]388        a,bz = dl_trainer.dl_models(filename=file,model=4,aug=augmentation,epochs=epochs,validation_split=validation_split)389        global filename2390        filename2 = a391        global b392        b = bz393        return redirect(url_for('resnet101'))394    return render_template('upload_resnet101.html',something=str(b))395396@app.route('/resnet152_classifier', methods=['GET', 'POST'])397def resnet152():398    global filename399    if request.method == 'POST':400        print(request.form.getlist('augmentation')[0])401        try:402            augmentation = int(request.form.getlist('augmentation')[0])403        except:404            augmentation = 1405        try:406            epochs = int(request.form.getlist('epochs')[0])407        except:408            epochs = 4409        print(request.form.getlist('epochs')[0])410        print(request.form.getlist('validation_split')[0])411        validation_split = float(request.form.getlist('validation_split')[0])412        import dl_trainer413        file = os.path.splitext(filename)[0]414        a,bz = dl_trainer.dl_models(filename=file,model=5,aug=augmentation,epochs=epochs,validation_split=validation_split)415        global filename2416        filename2 = a417        global b418        b = bz419        return redirect(url_for('resnet152'))420    return render_template('upload_resnet152.html',something=str(b))421422@app.route('/densenet121_classifier', methods=['GET', 'POST'])423def densenet121():424    global filename425    if request.method == 'POST':426        print(request.form.getlist('augmentation')[0])427        try:428            augmentation = int(request.form.getlist('augmentation')[0])429        except:430            augmentation = 1431        try:432            epochs = int(request.form.getlist('epochs')[0])433        except:434            epochs = 4435        print(request.form.getlist('epochs')[0])436        print(request.form.getlist('validation_split')[0])437        validation_split = float(request.form.getlist('validation_split')[0])438        import dl_trainer439        file = os.path.splitext(filename)[0]440        a,bz = dl_trainer.dl_models(filename=file,model=6,aug=augmentation,epochs=epochs,validation_split=validation_split)441        global filename2442        filename2 = a443        global b444        b = bz445        return redirect(url_for('densenet121'))446    return render_template('upload_densenet121.html',something=str(b))447448@app.route('/densenet169_classifier', methods=['GET', 'POST'])449def densenet169():450    global filename451    if request.method == 'POST':452        print(request.form.getlist('augmentation')[0])453        try:454            augmentation = int(request.form.getlist('augmentation')[0])455        except:456            augmentation = 1457        try:458            epochs = int(request.form.getlist('epochs')[0])459        except:460            epochs = 4461        print(request.form.getlist('epochs')[0])462        print(request.form.getlist('validation_split')[0])463        validation_split = float(request.form.getlist('validation_split')[0])464        import dl_trainer465        file = os.path.splitext(filename)[0]466        a,bz = dl_trainer.dl_models(filename=file,model=7,aug=augmentation,epochs=epochs,validation_split=validation_split)467        global filename2468        filename2 = a469        global b470        b = bz471        return redirect(url_for('densenet169'))472    return render_template('upload_densenet169.html',something=str(b))473474@app.route('/densenet201_classifier', methods=['GET', 'POST'])475def densenet201():476    global filename477    if request.method == 'POST':478        print(request.form.getlist('augmentation')[0])479        try:480            augmentation = int(request.form.getlist('augmentation')[0])481        except:482            augmentation = 1483        try:484            epochs = int(request.form.getlist('epochs')[0])485        except:486            epochs = 4487        print(request.form.getlist('epochs')[0])488        print(request.form.getlist('validation_split')[0])489        validation_split = float(request.form.getlist('validation_split')[0])490        import dl_trainer491        file = os.path.splitext(filename)[0]492        a,bz = dl_trainer.dl_models(filename=file,model=8,aug=augmentation,epochs=epochs,validation_split=validation_split)493        global filename2494        filename2 = a495        global b496        b = bz497        return redirect(url_for('densenet201'))498    return render_template('upload_densenet201.html',something=str(b))499500@app.route('/densenet161_classifier', methods=['GET', 'POST'])501def densenet161():502    global filename503    if request.method == 'POST':504        print(request.form.getlist('augmentation')[0])505        try:506            augmentation = int(request.form.getlist('augmentation')[0])507        except:508            augmentation = 1509        try:510            epochs = int(request.form.getlist('epochs')[0])511        except:512            epochs = 4513        print(request.form.getlist('epochs')[0])514        print(request.form.getlist('validation_split')[0])515        validation_split = float(request.form.getlist('validation_split')[0])516        import dl_trainer517        file = os.path.splitext(filename)[0]518        a,bz = dl_trainer.dl_models(filename=file,model=9,aug=augmentation,epochs=epochs,validation_split=validation_split)519        global filename2520        filename2 = a521        global b522        b = bz523        return redirect(url_for('densenet161'))524    return render_template('upload_densenet161.html',something=str(b))525526@app.route('/alexnet_classifier', methods=['GET', 'POST'])527def alexnet():528    global filename529    if request.method == 'POST':530        print(request.form.getlist('augmentation')[0])531        try:532            augmentation = int(request.form.getlist('augmentation')[0])533        except:534            augmentation = 1535        try:536            epochs = int(request.form.getlist('epochs')[0])537        except:538            epochs = 4539        print(request.form.getlist('epochs')[0])540        print(request.form.getlist('validation_split')[0])541        validation_split = float(request.form.getlist('validation_split')[0])542        import dl_trainer543        file = os.path.splitext(filename)[0]544        a,bz = dl_trainer.dl_models(filename=file,model=10,aug=augmentation,epochs=epochs,validation_split=validation_split)545        global filename2546        filename2 = a547        global b548        b = bz549        return redirect(url_for('alexnet'))550    return render_template('upload_alexnet.html',something=str(b))551552@app.route('/squeezenet1_0_classifier', methods=['GET', 'POST'])553def squeezenet1_0():554    global filename555    if request.method == 'POST':556        print(request.form.getlist('augmentation')[0])557        try:558            augmentation = int(request.form.getlist('augmentation')[0])559        except:560            augmentation = 1561        try:562            epochs = int(request.form.getlist('epochs')[0])563        except:564            epochs = 4565        print(request.form.getlist('epochs')[0])566        print(request.form.getlist('validation_split')[0])567        validation_split = float(request.form.getlist('validation_split')[0])568        import dl_trainer569        file = os.path.splitext(filename)[0]570        a,bz = dl_trainer.dl_models(filename=file,model=11,aug=augmentation,epochs=epochs,validation_split=validation_split)571        global filename2572        filename2 = a573        global b574        b = bz575        return redirect(url_for('squeezenet1_0'))576    return render_template('upload_squeezenet1_0.html',something=str(b))577578@app.route('/squeezenet1_1_classifier', methods=['GET', 'POST'])579def squeezenet1_1():580    global filename581    if request.method == 'POST':582        print(request.form.getlist('augmentation')[0])583        try:584            augmentation = int(request.form.getlist('augmentation')[0])585        except:586            augmentation = 1587        try:588            epochs = int(request.form.getlist('epochs')[0])589        except:590            epochs = 4591        print(request.form.getlist('epochs')[0])592        print(request.form.getlist('validation_split')[0])593        validation_split = float(request.form.getlist('validation_split')[0])594        import dl_trainer595        file = os.path.splitext(filename)[0]596        a,bz = dl_trainer.dl_models(filename=file,model=12,aug=augmentation,epochs=epochs,validation_split=validation_split)597        global filename2598        filename2 = a599        global b600        b = bz601        return redirect(url_for('squeezenet1_1'))602    return render_template('upload_squeezenet1_1.html',something=str(b))603604@app.route('/vgg11_classifier', methods=['GET', 'POST'])605def vgg11():606    global filename607    if request.method == 'POST':608        print(request.form.getlist('augmentation')[0])609        try:610            augmentation = int(request.form.getlist('augmentation')[0])611        except:612            augmentation = 1613        try:614            epochs = int(request.form.getlist('epochs')[0])615        except:616            epochs = 4617        print(request.form.getlist('epochs')[0])618        print(request.form.getlist('validation_split')[0])619        validation_split = float(request.form.getlist('validation_split')[0])620        import dl_trainer621        file = os.path.splitext(filename)[0]622        a,bz = dl_trainer.dl_models(filename=file,model=13,aug=augmentation,epochs=epochs,validation_split=validation_split)623        global filename2624        filename2 = a625        global b626        b = bz627        return redirect(url_for('vgg11'))628    return render_template('upload_vgg11.html',something=str(b))629630@app.route('/vgg11_bn_classifier', methods=['GET', 'POST'])631def vgg11_bn():632    global filename633    if request.method == 'POST':634        print(request.form.getlist('augmentation')[0])635        try:636            augmentation = int(request.form.getlist('augmentation')[0])637        except:638            augmentation = 1639        try:640            epochs = int(request.form.getlist('epochs')[0])641        except:642            epochs = 4643        print(request.form.getlist('epochs')[0])644        print(request.form.getlist('validation_split')[0])645        validation_split = float(request.form.getlist('validation_split')[0])646        import dl_trainer647        file = os.path.splitext(filename)[0]648        a,bz = dl_trainer.dl_models(filename=file,model=14,aug=augmentation,epochs=epochs,validation_split=validation_split)649        global filename2650        filename2 = a651        global b652        b = bz653        return redirect(url_for('vgg11_bn'))654    return render_template('upload_vgg11_bn.html',something=str(b))655656@app.route('/vgg13_classifier', methods=['GET', 'POST'])657def vgg13():658    global filename659    if request.method == 'POST':660        print(request.form.getlist('augmentation')[0])661        try:662            augmentation = int(request.form.getlist('augmentation')[0])663        except:664            augmentation = 1665        try:666            epochs = int(request.form.getlist('epochs')[0])667        except:668            epochs = 4669        print(request.form.getlist('epochs')[0])670        print(request.form.getlist('validation_split')[0])671        validation_split = float(request.form.getlist('validation_split')[0])672        import dl_trainer673        file = os.path.splitext(filename)[0]674        a,bz = dl_trainer.dl_models(filename=file,model=15,aug=augmentation,epochs=epochs,validation_split=validation_split)675        global filename2676        filename2 = a677        global b678        b = bz679        return redirect(url_for('vgg13'))680    return render_template('upload_vgg13.html',something=str(b))681682@app.route('/vgg13_bn_classifier', methods=['GET', 'POST'])683def vgg13_bn():684    global filename685    if request.method == 'POST':686        print(request.form.getlist('augmentation')[0])687        try:688            augmentation = int(request.form.getlist('augmentation')[0])689        except:690            augmentation = 1691        try:692            epochs = int(request.form.getlist('epochs')[0])693        except:694            epochs = 4695        print(request.form.getlist('epochs')[0])696        print(request.form.getlist('validation_split')[0])697        validation_split = float(request.form.getlist('validation_split')[0])698        import dl_trainer699        file = os.path.splitext(filename)[0]700        a,bz = dl_trainer.dl_models(filename=file,model=16,aug=augmentation,epochs=epochs,validation_split=validation_split)701        global filename2702        filename2 = a703        global b704        b = bz705        return redirect(url_for('vgg13_bn'))706    return render_template('upload_vgg13_bn.html',something=str(b))707708@app.route('/vgg16_classifier', methods=['GET', 'POST'])709def vgg16():710    global filename711    if request.method == 'POST':712        print(request.form.getlist('augmentation')[0])713        try:714            augmentation = int(request.form.getlist('augmentation')[0])715        except:716            augmentation = 1717        try:718            epochs = int(request.form.getlist('epochs')[0])719        except:720            epochs = 4721        print(request.form.getlist('epochs')[0])722        print(request.form.getlist('validation_split')[0])723        validation_split = float(request.form.getlist('validation_split')[0])724        import dl_trainer725        file = os.path.splitext(filename)[0]726        a,bz = dl_trainer.dl_models(filename=file,model=17,aug=augmentation,epochs=epochs,validation_split=validation_split)727        global filename2728        filename2 = a729        global b730        b = bz731        return redirect(url_for('vgg16'))732    return render_template('upload_vgg16.html',something=str(b))733734@app.route('/vgg16_bn_classifier', methods=['GET', 'POST'])735def vgg16_bn():736    global filename737    if request.method == 'POST':738        print(request.form.getlist('augmentation')[0])739        try:740            augmentation = int(request.form.getlist('augmentation')[0])741        except:742            augmentation = 1743        try:744            epochs = int(request.form.getlist('epochs')[0])745        except:746            epochs = 4747        print(request.form.getlist('epochs')[0])748        print(request.form.getlist('validation_split')[0])749        validation_split = float(request.form.getlist('validation_split')[0])750        import dl_trainer751        file = os.path.splitext(filename)[0]752        a,bz = dl_trainer.dl_models(filename=file,model=18,aug=augmentation,epochs=epochs,validation_split=validation_split)753        global filename2754        filename2 = a755        global b756        b = bz757        return redirect(url_for('vgg16_bn'))758    return render_template('upload_vgg16_bn.html',something=str(b))759760@app.route('/vgg19_classifier', methods=['GET', 'POST'])761def vgg19():762    global filename763    if request.method == 'POST':764        print(request.form.getlist('augmentation')[0])765        try:766            augmentation = int(request.form.getlist('augmentation')[0])767        except:768            augmentation = 1769        try:770            epochs = int(request.form.getlist('epochs')[0])771        except:772            epochs = 4773        print(request.form.getlist('epochs')[0])774        print(request.form.getlist('validation_split')[0])775        validation_split = float(request.form.getlist('validation_split')[0])776        import dl_trainer777        file = os.path.splitext(filename)[0]778        a,bz = dl_trainer.dl_models(filename=file,model=19,aug=augmentation,epochs=epochs,validation_split=validation_split)779        global filename2780        filename2 = a781        global b782        b = bz783        return redirect(url_for('vgg19'))784    return render_template('upload_vgg19.html',something=str(b))785786@app.route('/vgg19_bn_classifier', methods=['GET', 'POST'])787def vgg19_bn():788    global filename789    if request.method == 'POST':790        print(request.form.getlist('augmentation')[0])791        try:792            augmentation = int(request.form.getlist('augmentation')[0])793        except:794            augmentation = 1795        try:796            epochs = int(request.form.getlist('epochs')[0])797        except:798            epochs = 4799        print(request.form.getlist('epochs')[0])800        print(request.form.getlist('validation_split')[0])801        validation_split = float(request.form.getlist('validation_split')[0])802        import dl_trainer803        file = os.path.splitext(filename)[0]804        a,bz = dl_trainer.dl_models(filename=file,model=20,aug=augmentation,epochs=epochs,validation_split=validation_split)805        global filename2806        filename2 = a807        global b808        b = bz809        return redirect(url_for('vgg19_bn'))810    return render_template('upload_vgg19_bn.html',something=str(b))811812if __name__ == "__main__":813    app.run()
...

NeuralNetUtil.py

Source:NeuralNetUtil.py

1#utility functions for neural net project2import random3def getNNPenData(fileString="datasets/pendigits.txt", limit=100000):4    """5    returns limit # of examples from penDigits file6    """7    examples=[]8    data = open(fileString)9    lineNum = 010    for line in data:11        inVec = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]12        outVec = [0,0,0,0,0,0,0,0,0,0]                      #which digit is output13        count=014        for val in line.split(','):15            if count==16:16                outVec[int(val)] = 117            else:18                inVec[count] = int(val)/100.0               #need to normalize values for inputs19            count+=120        examples.append((inVec,outVec))21        lineNum += 122        if (lineNum >= limit):23            break24    return examples2526def getList(num,length):27    list = [0]*length28    list[num-1] = 129    return list30    31def getNNCarData(fileString ="datasets/car.data.txt", limit=100000 ):32    """33    returns limit # of examples from file passed as string34    """35    examples=[]36    attrValues={}37    data = open(fileString)38    attrs = ['buying','maint','doors','persons','lug_boot','safety']39    attr_values = [['vhigh', 'high', 'med', 'low'],40                 ['vhigh', 'high', 'med', 'low'],41                 ['2','3','4','5more'],42                 ['2','4','more'],43                 ['small', 'med', 'big'],44                 ['high', 'med', 'low']]45    46    attrNNList = [('buying', {'vhigh' : getList(1,4), 'high' : getList(2,4), 'med' : getList(3,4), 'low' : getList(4,4)}),47                 ('maint',{'vhigh' : getList(1,4), 'high' : getList(2,4), 'med' : getList(3,4), 'low' : getList(4,4)}),48                 ('doors',{'2' : getList(1,4), '3' : getList(2,4), '4' : getList(3,4), '5more' : getList(4,4)}),49                 ('persons',{'2' : getList(1,3), '4' : getList(2,3), 'more' : getList(3,3)}),50                 ('lug_boot',{'small' : getList(1,3),'med' : getList(2,3),'big' : getList(3,3)}),51                 ('safety',{'high' : getList(1,3), 'med' : getList(2,3),'low' : getList(3,3)})]5253    classNNList = {'unacc' : [1,0,0,0], 'acc' : [0,1,0,0], 'good' : [0,0,1,0], 'vgood' : [0,0,0,1]}54    55    for index in range(len(attrs)):56        attrValues[attrs[index]]=attrNNList[index][1]5758    lineNum = 059    for line in data:60        inVec = []61        outVec = []62        count=063        for val in line.split(','):64            if count==6:65                outVec = classNNList[val[:val.find('\n')]]66            else:67                inVec.append(attrValues[attrs[count]][val])68            count+=169        examples.append((inVec,outVec))70        lineNum += 171        if (lineNum >= limit):72            break73    random.shuffle(examples)74    return examples757677def buildExamplesFromPenData(size=10000):78    """79    build Neural-network friendly data struct80            81    pen data format82    16 input(attribute) values from 0 to 10083    10 possible output values, corresponding to a digit from 0 to 98485    """86    if (size != 10000):87        penDataTrainList = getNNPenData("datasets/pendigitsTrain.txt",int(.8*size))88        penDataTestList = getNNPenData("datasets/pendigitsTest.txt",int(.2*size))89    else :    90        penDataTrainList = getNNPenData("datasets/pendigitsTrain.txt")91        penDataTestList = getNNPenData("datasets/pendigitsTest.txt")92    return penDataTrainList, penDataTestList939495def buildExamplesFromCarData(size=200):96    """97    build Neural-network friendly data struct98            99    car data format100    | names file (C4.5 format) for car evaluation domain101102    | class values - 4 value output vector103104    unacc, acc, good, vgood105106    | attributes107108    buying:   vhigh, high, med, low.109    maint:    vhigh, high, med, low.110    doors:    2, 3, 4, 5more.111    persons:  2, 4, more.112    lug_boot: small, med, big.113    safety:   low, med, high.114    """115    carData = getNNCarData()116    carDataTrainList = []117    for cdRec in carData:118        tmpInVec = []119        for cdInRec in cdRec[0] :120            for val in cdInRec :121                tmpInVec.append(val)122        #print "in :" + str(cdRec) + " in vec : " + str(tmpInVec)123        tmpList = (tmpInVec, cdRec[1])124        carDataTrainList.append(tmpList)125    #print "car data list : " + str(carDataList)126    tests = len(carDataTrainList)-size127    carDataTestList = [carDataTrainList.pop(random.randint(0,tests+size-t-1)) for t in xrange(tests)]128    return carDataTrainList, carDataTestList129    130131def buildPotentialHiddenLayers(numIns, numOuts):132    """133    This builds a list of lists of hidden layer layouts134    numIns - number of inputs for data135    some -suggestions- for hidden layers - no more than 2/3 # of input nodes per layer, and136    no more than 2x number of input nodes total (so up to 3 layers of 2/3 # ins max137    """138    resList = []139    tmpList = []140    maxNumNodes = max(numOuts+1, 2 * numIns)141    if (maxNumNodes > 15):142        maxNumNodes = 15143144    for lyr1cnt in range(numOuts,maxNumNodes):145        for lyr2cnt in range(numOuts-1,lyr1cnt+1):146            for lyr3cnt in range(numOuts-1,lyr2cnt+1):147                if (lyr2cnt == numOuts-1):148                    lyr2cnt = 0149                150                if (lyr3cnt == numOuts-1):151                    lyr3cnt = 0152                tmpList.append(lyr1cnt)153                tmpList.append(lyr2cnt)154                tmpList.append(lyr3cnt)155                resList.append(tmpList)156                tmpList = []157    return resList158159def getNNExtraData(fileString ="datasets/extra.txt", limit=10000 ):160    """161    returns limit # of examples from file passed as string162    """163    examples=[]164    attrValues={}165    data = open(fileString)166    attrs = ['top-left-square','top-middle-square','top-right-square','middle-left-square','middle-middle-square','middle-right-square',167                'bottom-left-square', 'bottom-middle-square', 'bottom-right-square']168    attr_values = [['x', 'o', 'b'],169                 ['x', 'o', 'b'],170                 ['x', 'o', 'b'],171                 ['x', 'o', 'b'],172                 ['x', 'o', 'b'],173                 ['x', 'o', 'b'],174                 ['x', 'o', 'b'],175                 ['x', 'o', 'b'],176                 ['x', 'o', 'b']]177    178    attrNNList = [('top-left-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)}),179                 ('top-middle-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)}),180                 ('top-right-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)}),181                 ('middle-left-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)}),182                 ('middle-middle-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)}),183                 ('middle-right-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)}),184                 ('bottom-left-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)}),185                 ('bottom-middle-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)}),186                 ('bottom-right-square', {'x' : getList(1,3), 'o' : getList(2,3), 'b' : getList(3,3)})]187188    classNNList = {'positive': [1,0], 'negative': [0,1]}189    190    for index in range(len(attrs)):191        attrValues[attrs[index]]=attrNNList[index][1]192193    lineNum = 0194    for line in data:195        inVec = []196        outVec = []197        count=0198        for val in line.split(','):199            if count==9:200                #print(lineNum)201                outVec = classNNList[val.strip()]202            else:203                inVec.append(attrValues[attrs[count]][val])204            count+=1205        examples.append((inVec,outVec))206        lineNum += 1207        if (lineNum >= limit):208            break209    random.shuffle(examples)210    return examples211212def getNNXORData(fileString="datasets/xordata.txt", limit=100000):213    """214    returns limit # of examples from penDigits file215    """216    examples=[]217    attrValues={}218    data = open(fileString)219    attrs = ['X','Y']220    attr_values = [['0', '1'], ['0', '1']]221    222    attrNNList = [('X', {'0' : getList(1,2), '1' : getList(2,2)}), ('Y',{'0' : getList(1,2), '1' : getList(2,2)})]223224    classNNList = {'0' : [1,0], '1' : [0,1]}225    226    for index in range(len(attrs)):227        attrValues[attrs[index]]=attrNNList[index][1]228229    lineNum = 0230    for line in data:231        inVec = []232        outVec = []233        count=0234        for val in line.split(','):235            if count==2:236                #print(type(val[:val.find('\n')]))237                outVec = classNNList[val.strip()]238            else:239                inVec.append(attrValues[attrs[count]][val])240            count+=1241        examples.append((inVec,outVec))242        lineNum += 1243        if (lineNum >= limit):244            break245    return examples246247def buildExamplesFromXORData(size=4):248    """249    build Neural-network friendly data struct250            251    pen data format252    16 input(attribute) values from 0 to 100253    10 possible output values, corresponding to a digit from 0 to 9254255    """256    XORData = getNNXORData()257    XORDataTrainList = []258    for cdRec in XORData:259        tmpInVec = []260        for cdInRec in cdRec[0] :261            for val in cdInRec :262                tmpInVec.append(val)263        #print "in :" + str(cdRec) + " in vec : " + str(tmpInVec)264        tmpList = (tmpInVec, cdRec[1])265        XORDataTrainList.append(tmpList)266    #print "car data list : " + str(carDataList)267    #tests = len(XORDataTrainList)-size268    XORDataTestList = XORDataTrainList269    return XORDataTrainList, XORDataTestList270271def buildExamplesFromExtraData(size = 200):272    extraData = getNNExtraData()273    extraDataTrainList = []274    for cdRec in extraData:275        tmpInVec = []276        for cdInRec in cdRec[0] :277            for val in cdInRec :278                tmpInVec.append(val)279        #print "in :" + str(cdRec) + " in vec : " + str(tmpInVec)280        tmpList = (tmpInVec, cdRec[1])281        extraDataTrainList.append(tmpList)282    #print "car data list : " + str(carDataList)283    tests = len(extraDataTrainList)-size284    extraDataTestList = [extraDataTrainList.pop(random.randint(0,tests+size-t-1)) for t in xrange(tests)]285    return extraDataTrainList, extraDataTestList
...

bitter.cgi

Source:bitter.cgi

...24# --------------------------------------------------------------------------------------------25# Functions to handle all the back-end functions i.e. controller26# Each html form is an "operation" and the following ifs handle each operation appropriately27# --------------------------------------------------------------------------------------------28if "operation" in form and "Log In" in form.getlist("operation"):29   if userActions.checkLogin(form.getfirst("username"), form.getfirst("password")):30      cookieCreated = userActions.createSessionCookie(form.getfirst("username"))31      html = viewPage.userHome(form.getfirst("username"))32   else:33      html = viewPage.message("Incorrect Username or Password")34            35elif "operation" in form and "Sign Up" in form.getlist("operation"):36   if userActions.signUp(form.getfirst("username"), form.getfirst("fullName"), 37                                                form.getfirst("email"), form.getfirst("password")):38      html = viewPage.message("Account Created, Verification email sent")39   else:40      html = viewPage.message("Sorry that username is unavailable")41elif "operation" in form and "Log Out" in form.getlist("operation"):42   if userActions.isLoggedIn():43      userActions.logOut(userActions.getCurrentUser())   44      cookieCreated = userActions.deleteSessionCookie()45      loginFile = open("html/login.html","r")46      html = loginFile.read()47      48elif "operation" in form and "search" in form.getlist("operation"):49   html = viewPage.search(form.getfirst("searchQuery"))50elif "operation" in form and "View Profile" in form.getlist("operation"):51   html = viewPage.userProfile(form.getfirst("username"))52elif "operation" in form and "Home" in form.getlist("operation"):53   html = viewPage.userHome(userActions.getCurrentUser())54elif "operation" in form and "Bleat" in form.getlist("operation"):55   bleatActions.insertBleat(userActions.getCurrentUser(),form.getfirst("bleatStr"))56   html = viewPage.userHome(userActions.getCurrentUser())   57   #html = viewPage.test(userActions.getCurrentUser(), form.getfirst("bleatStr"))58elif "operation" in form and "Unlisten" in form.getlist("operation"):59   userActions.unlisten(form.getfirst("username"))60   html = viewPage.userProfile(form.getfirst("username")) # TEMP61   #show msg page/use js instead62elif "operation" in form and "Listen" in form.getlist("operation"):63   userActions.listen(form.getfirst("username"))64   html = viewPage.userProfile(form.getfirst("username")) #TEMP65   #show msg page/ use js instead66elif "operation" in form and "Reply" in form.getlist("operation"):67   html = viewPage.reply(form.getfirst("bleatID"))68elif "operation" in form and "Reply To Bleat" in form.getlist("operation"):69   bleatActions.replyToBleat(userActions.getCurrentUser(), form.getfirst("bleatid"), 70                                                                        form.getfirst("bleatStr"))71   html = viewPage.userHome(userActions.getCurrentUser())72elif "operation" in form and "verify" in form.getlist("operation"):73   userActions.verify(form.getfirst("user"))74   html = viewPage.message("Verified!")75   #show msg page76elif "operation" in form and "Settings" in form.getlist("operation"):77   html = viewPage.settings()78elif "operation" in form and "Update Account" in form.getlist("operation"):   # TO DO79   userActions.updateAccount(userActions.getCurrentUser(), form.getfirst("password"), form.getfirst("email"), form.getfirst("fullName"), form.getfirst("homeLatitude"), form.getfirst("homeLongitude"),80                                                                                                                                          form.getfirst("homeSuburb"), form.getfirst("profileText"))81   html = viewPage.settings()82elif "operation" in form and "Suspend Account" in form.getlist("operation"):83   userActions.suspendAccount(userActions.getCurrentUser())84   html = viewPage.settings()85   86elif "operation" in form and "Unsuspend Account" in form.getlist("operation"):87   userActions.unsuspendAccount(userActions.getCurrentUser())88   html = viewPage.settings()89   90elif "operation" in form and "Delete Account" in form.getlist("operation"):   #UNTESTED91   user = userActions.getCurrentUser()92   userActions.logOut(user) 93   userActions.deleteAccount(user)94   cookieCreated = userActions.deleteSessionCookie()95   loginFile = open("html/login.html","r")96   html = loginFile.read()97elif "operation" in form and "RecoverPassword" in form.getlist("operation"):98   if userActions.recoverPassword(form.getfirst("username")):99      html = viewPage.message("An email has been sent to your email address with instructions on how to recover your password")100   else:101      html = viewPage.message("Username doesn't exist")102elif "operation" in form and "Forgot Password" in form.getlist("operation"):103   forgotPassFile = open("html/forgotPassword.html")104   html = forgotPassFile.read()105elif "operation" in form and "resetPasswordView" in form.getlist("operation"):106   html = viewPage.resetPasswordView(form.getfirst("user"))107elif "operation" in form and "resetPassword" in form.getlist("operation"):108   userActions.resetPassword(form.getfirst("username"), form.getfirst("password"))109   loginFile = open("html/login.html","r")110   html = loginFile.read()111   112elif userActions.isLoggedIn():   #otherwise show the user their home page113   html = viewPage.userHome(userActions.getCurrentUser())114else: #otherwise show the login page115   loginFile = open("html/login.html","r")116   html = loginFile.read()117# Printing the HTML generated from the controller above118httpHeader(cookieCreated)...

restaurantLike.js

Source:restaurantLike.js

1let cnt = 0;2let tmpNum = -1;3function locationLoadSuccess(pos) {4    // íì¬ ìì¹ ë°ìì¤ê¸°5    var currentPos = new kakao.maps.LatLng(pos.coords.latitude, pos.coords.longitude);6    mylat = pos.coords.latitude;7    mylong = pos.coords.longitude;8    console.log("íì¬ìì¹ : " + currentPos + " íì: " + typeof currentPos);9    restaurantSearch(mylat, mylong);10};11function locationLoadError(pos) {12    alert('ìì¹ ì ë³´ë¥¼ ê°ì ¸ì¤ëë° ì¤í¨íìµëë¤.');13};14function searchRes(likelist) {15    console.log(likelist);16    navigator.geolocation.getCurrentPosition(locationLoadSuccess, locationLoadError);17};18function restaurantSearch(myY, myX) {19    console.log("**" + myY, myX);20    $.ajax({21        method: 'GET'22        , url: "https://dapi.kakao.com/v2/local/search/keyword.json"23        , data: {24            query: $("#restName").val() //ì¬ì©ìê° ê²ìí í¤ìë25            , category_group_code: "FD6" //ììì  íí°ë§26            , x: myX //ì¤ì¬ì¢í X27            , y: myY //ì¤ì¬ì¢í Y28            , sort: "distance" //ê±°ë¦¬ì29        }30        , headers: {Authorization: "KakaoAK f1b2afc29adbbda05eea78825d075ca9"}31    })32        .done(function (data) {33            var getList = "";34            getList += "<table style='display:inline-block; border-collapse: separate; border-spacing: 0 10px;'>"35            for (var i = 0; i < data.documents.length; i++) {36                getList += "<tr>"37                getList += "<td> <a href='/detail?restaurant_id=" + data.documents[i].id + "' style='color:blue; text-decoration: none;'>" + data.documents[i].place_name + "</a></td>"38                getList += "<input type='hidden' value='" + data.documents[i].id + "'>"39                getList += "<input type='hidden' value='" + data.documents[i].place_name + "'>"40                getList += "<input type='hidden' value='" + data.documents[i].x + "'>"41                getList += "<input type='hidden' value='" + data.documents[i].y + "'>"42                getList += "<td>" + data.documents[i].phone + "</td>"43                getList += "<td>" + data.documents[i].category_name + "</td>"44                getList += "<td>" + data.documents[i].address_name + "</td>"45                getList += "<td>"46                getList += "<img src='like/default_like.png' id='likeimg" + i + "' width='50' height='50' onclick='javascript:saveData(" + i + ")' style='cursor: pointer'>"47                getList += "</td>"48                getList += "</tr>"49            }50            getList += "</table>"51            $("#restList").html("");52            $("#restList").html(getList);53        })54}55function enterkey() {56    if (window.event.keyCode == 13) {57        searchRes();58    }59}60function saveData(num) {61    var no = num * 5;62    var inputNum = num * 4 + 1;63    /*var str1 = document.getElementsByTagName('td')[no].childNodes[0].nodeValue; // id64    var str2 = document.getElementsByTagName('td')[no + 1].childNodes[0].nodeValue; // name*/65    var str3 = document.getElementsByTagName('td')[no + 1].childNodes[0].nodeValue; // phone66    var str4 = document.getElementsByTagName('td')[no + 3].childNodes[0].nodeValue; // address67    var str1 = document.getElementsByTagName('input')[inputNum + 1].value; // id68    var str2 = document.getElementsByTagName('input')[inputNum + 2].value; // name69    var x = document.getElementsByTagName('input')[inputNum + 3].value; // x70    var y = document.getElementsByTagName('input')[inputNum + 4].value; // y71    /*alert(x + ", "+ y);72    alert("ID: " + str1 + ", NAME: "+str2 + ", phone: "+str3 + ", ì£¼ì: "+str4);*/73    const dataStr = {74        "restaurant_id": str1,75        "restaurant_name": str2,76        "phone": str3,77        "x": x,78        "y": y,79        "address": str480    }81    if (document.getElementById('likeimg' + num).src === "http://localhost:8084/like/default_like.png") {82        cnt += 1;83        $.ajax({84            method: 'POST',85            url: "/like",86            contentType: "application/json",87            dataType: "json",88            data: JSON.stringify(dataStr),89            success: function (data) {90                console.log("ì°íê¸° ì±ê³µ");91            },92            error: function (xhr, status, error) {93                console.log("ìë¬ë°ì");94            }95        });96        document.getElementById('likeimg' + num).src = 'like/like.png'97    }98    else {99        $.ajax({100            method: 'GET',101            url: "/myLikeDelete",102            contentType: "application/json",103            dataType: "json",104            data: {'restaurant_id': str1},105            success: function (data) {106                // if(data.proc == "success") {107                //     console.log("DB ì ì¥ìë£")108                // }109            },110            error: function (xhr, status, error) {111                console.log("ìë¬ë°ì");112            }113        });114        cnt = 0;115        document.getElementById('likeimg' + num).src = 'like/default_like.png'116    }117    tmpNum = num;118    location.href = "#";119}120function checkdata(str){121    $.ajax({122        method: 'POST',123        url: "/checklikes",124        contentType: "application/json",125        dataType: "json",126        data: {'restaurant_id': str},127        success: function (data) {128            // if(data.proc == "success") {129            //     console.log("DB ì ì¥ìë£")130            // }131            return true;132        },133        error: function (xhr, status, error) {134            console.log("ìë¬ë°ì!!");135        }136    });137    return false;...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.