mirror of https://github.com/RE-OWOD/RE-OWOD
43 lines
1.6 KiB
Python
43 lines
1.6 KiB
Python
import cv2
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import sys
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# from drawBoxes import draw_boxes
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import time
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import torch
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import matplotlib.pyplot as plt
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from selective_search import selective_search
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import numpy as np
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t1_train_file_path = "/home/selective_search/all_task_test.txt"
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with open(t1_train_file_path, 'r') as t1_train_file:
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t1_train_list = t1_train_file.read().splitlines()
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for image_num,image_name in enumerate(t1_train_list):
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image_name = t1_train_list[image_num]
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image_path = "/home//datasets/VOC2007/JPEGImages/" + image_name + ".jpg"
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img = cv2.imread(image_path)[:, :, ::-1]
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img_rgb = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
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try:
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boxes = selective_search(img_rgb, mode='single', random_sort=False)
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new_flag = True
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for boxes_i in boxes:
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if new_flag:
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boxes_sum = np.array(boxes_i).reshape(1,4)
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new_flag = False
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else:
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boxes_sum = np.r_[boxes_sum,np.array(boxes_i).reshape(1,4)]
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boxes_draw = boxes_sum[:50,:]
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img_save = {'image_size':img.shape[0:2],'obj_boxes':boxes_draw}
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except:
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print("cannot compute score:",image_name)
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boxes_draw = []
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img_save = {'image_size':img.shape[0:2],'obj_boxes':boxes_draw}
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error_save_path = "/home/selective_search_save/selective_search_test_error/" + image_name + ".pickle"
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torch.save(img_save, error_save_path)
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img_save_path = "/home/selective_search_save/selective_search_test/" + image_name + ".pickle"
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torch.save(img_save, img_save_path)
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print("image_num:",image_num)
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