Best Python code snippet using ATX
example.py
Source:example.py  
1# coding: utf-82__author__ = 'ZFTurbo: https://kaggle.com/zfturbo'3import cv24import numpy as np5from ensemble_boxes import *6def show_image(im, name='image'):7    cv2.imshow(name, im.astype(np.uint8))8    cv2.waitKey(0)9    cv2.destroyAllWindows()10def gen_color_list(model_num, labels_num):11    color_list = np.zeros((model_num, labels_num, 3))12    colors_to_use = [(255, 0, 0), (0, 255, 0), (0, 0, 255), (0, 255, 255), (255, 0, 255), (255, 255, 0), (0, 0, 0)]13    total = 014    for i in range(model_num):15        for j in range(labels_num):16            color_list[i, j, :] = colors_to_use[total]17            total = (total + 1) % len(colors_to_use)18    return color_list19def show_boxes(boxes_list, scores_list, labels_list, image_size=800):20    thickness = 521    color_list = gen_color_list(len(boxes_list), len(np.unique(labels_list)))22    image = np.zeros((image_size, image_size, 3), dtype=np.uint8)23    image[...] = 25524    for i in range(len(boxes_list)):25        for j in range(len(boxes_list[i])):26            x1 = int(image_size * boxes_list[i][j][0])27            y1 = int(image_size * boxes_list[i][j][1])28            x2 = int(image_size * boxes_list[i][j][2])29            y2 = int(image_size * boxes_list[i][j][3])30            lbl = labels_list[i][j]31            cv2.rectangle(image, (x1, y1), (x2, y2), color_list[i][lbl], int(thickness * scores_list[i][j]))32    show_image(image)33def example_wbf_2_models(iou_thr=0.55, draw_image=True):34    """35    This example shows how to ensemble boxes from 2 models using WBF method    36    :return: 37    """38    boxes_list = [39        [40            [0.00, 0.51, 0.81, 0.91],41            [0.10, 0.31, 0.71, 0.61],42            [0.01, 0.32, 0.83, 0.93],43            [0.02, 0.53, 0.11, 0.94],44            [0.03, 0.24, 0.12, 0.35],45        ],46        [47            [0.04, 0.56, 0.84, 0.92],48            [0.12, 0.33, 0.72, 0.64],49            [0.38, 0.66, 0.79, 0.95],50            [0.08, 0.49, 0.21, 0.89],51        ],52    ]53    scores_list = [54        [55            0.9,56            0.8,57            0.2,58            0.4,59            0.7,60        ],61        [62            0.5,63            0.8,64            0.7,65            0.3,66        ]67    ]68    labels_list = [69        [70            0,71            1,72            0,73            1,74            1,75        ],76        [77            1,78            1,79            1,80            0,81        ]82    ]83    weights = [2, 1]84    if draw_image:85        show_boxes(boxes_list, scores_list, labels_list)86    boxes, scores, labels = weighted_boxes_fusion(boxes_list, scores_list, labels_list, weights=weights, iou_thr=iou_thr, skip_box_thr=0.0)87    if draw_image:88        show_boxes([boxes], [scores], [labels.astype(np.int32)])89    print(len(boxes))90    print(boxes)91def example_wbf_1_model(iou_thr=0.55, draw_image=True):92    """93    This example shows how to ensemble boxes from single model using WBF method    94    :return: 95    """96    boxes_list = [97        [0.00, 0.51, 0.81, 0.91],98        [0.10, 0.31, 0.71, 0.61],99        [0.01, 0.32, 0.83, 0.93],100        [0.02, 0.53, 0.11, 0.94],101        [0.03, 0.24, 0.12, 0.35],102        [0.04, 0.56, 0.84, 0.92],103        [0.12, 0.33, 0.72, 0.64],104        [0.38, 0.66, 0.79, 0.95],105        [0.08, 0.49, 0.21, 0.89],106    ]107    scores_list = [0.9, 0.8, 0.2, 0.4, 0.7, 0.5, 0.8, 0.7, 0.3]108    labels_list = [0, 1, 0, 1, 1, 1, 1, 1, 0]109    if draw_image:110        show_boxes([boxes_list], [scores_list], [labels_list])111    boxes, scores, labels = weighted_boxes_fusion([boxes_list], [scores_list], [labels_list], weights=None, iou_thr=iou_thr, skip_box_thr=0.0)112    if draw_image:113        show_boxes([boxes], [scores], [labels.astype(np.int32)])114    print(len(boxes))115    print(boxes)116def example_nms_2_models(method, iou_thr=0.5, sigma=0.5, thresh=0.001, draw_image=True):117    """118    This example shows how to ensemble boxes from 2 models using NMS method    119    :return: 120    """121    boxes_list = [122        [123            [0.00, 0.51, 0.81, 0.91],124            [0.10, 0.31, 0.71, 0.61],125            [0.01, 0.32, 0.83, 0.93],126            [0.02, 0.53, 0.11, 0.94],127            [0.03, 0.24, 0.12, 0.35],128        ],129        [130            [0.04, 0.56, 0.84, 0.92],131            [0.12, 0.33, 0.72, 0.64],132            [0.38, 0.66, 0.79, 0.95],133            [0.08, 0.49, 0.21, 0.89],134        ],135    ]136    scores_list = [137        [138            0.9,139            0.8,140            0.2,141            0.4,142            0.7,143        ],144        [145            0.5,146            0.8,147            0.7,148            0.3,149        ]150    ]151    labels_list = [152        [153            0,154            1,155            0,156            1,157            1,158        ],159        [160            1,161            1,162            1,163            0,164        ]165    ]166    weights = [2, 1]167    if draw_image:168        show_boxes(boxes_list, scores_list, labels_list)169    boxes, scores, labels = nms_method(boxes_list, scores_list, labels_list, method=method, weights=weights, iou_thr=iou_thr, sigma=sigma, thresh=thresh)170    if draw_image:171        show_boxes([boxes], [scores], [labels.astype(np.int32)])172    print(len(boxes))173    print(boxes)174if __name__ == '__main__':175    draw_image = True176    example_wbf_2_models(draw_image=draw_image)177    example_wbf_1_model(draw_image=draw_image)178    example_nms_2_models(draw_image=draw_image, method=3, iou_thr=0.5, thresh=0.0)...Learn to execute automation testing from scratch with LambdaTest Learning Hub. 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