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import math
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import os
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import cv2
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import numpy as np
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root_dir = '/export2/home/wht/oulu_images_crop/'
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img_root = '/export2/home/wht/oulu_images/train_img_flod/'
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map_root = '/export2/home/wht/oulu_images/train_depth_flod/'
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bbox_root = '/export2/home/wht/oulu_images/train_bbox_flod/'
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def crop_face_from_scene(image, face_name_full, scale):
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f = open(face_name_full, 'r')
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lines = f.readlines()
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lines = lines[0].split(' ')
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y1, x1, w, h = [int(ele) for ele in lines[:4]]
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f.close()
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y2 = y1 + w
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x2 = x1 + h
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y_mid = (y1 + y2) / 2.0
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x_mid = (x1 + x2) / 2.0
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h_img, w_img = image.shape[0], image.shape[1]
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w_scale = scale * w
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h_scale = scale * h
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y1 = y_mid - w_scale / 2.0
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x1 = x_mid - h_scale / 2.0
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y2 = y_mid + w_scale / 2.0
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x2 = x_mid + h_scale / 2.0
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y1 = max(math.floor(y1), 0)
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x1 = max(math.floor(x1), 0)
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y2 = min(math.floor(y2), w_img)
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x2 = min(math.floor(x2), h_img)
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region = image[x1:x2, y1:y2]
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return region
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def crop_face_from_scene_prnet(image, face_name_full, scale):
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h_img, w_img = image.shape[0], image.shape[1]
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f = open(face_name_full, 'r')
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lines = f.readlines()
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lines = lines[0].split(' ')
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l, r, t, b = [int(ele) for ele in lines[:4]]
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if l < 0:
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l = 0
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if r > w_img:
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r = w_img
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if t < 0:
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t = 0
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if b > h_img:
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b = h_img
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y1 = l
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x1 = t
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w = r - l
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h = b - t
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f.close()
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y2 = y1 + w
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x2 = x1 + h
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y_mid = (y1 + y2) / 2.0
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x_mid = (x1 + x2) / 2.0
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w_scale = scale * w
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h_scale = scale * h
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y1 = y_mid - w_scale / 2.0
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x1 = x_mid - h_scale / 2.0
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y2 = y_mid + w_scale / 2.0
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x2 = x_mid + h_scale / 2.0
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y1 = max(math.floor(y1), 0)
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x1 = max(math.floor(x1), 0)
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y2 = min(math.floor(y2), w_img)
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x2 = min(math.floor(x2), h_img)
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region = image[x1:x2, y1:y2]
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return region
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vedio_list = os.listdir(bbox_root)
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for i, vedio_name in enumerate(vedio_list):
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print(i)
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bbox_list = os.listdir(os.path.join(bbox_root, vedio_name))
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for bbox_name in bbox_list:
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face_scale = np.random.randint(12, 15)
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face_scale = face_scale / 10.0
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bbox_path = os.path.join(bbox_root, vedio_name, bbox_name)
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img_path = os.path.join(img_root, vedio_name, bbox_name[:-4] + '.jpg')
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img = cv2.imread(img_path)
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img_crop = cv2.resize(crop_face_from_scene_prnet(img, bbox_path, face_scale), (256, 256))
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img_crop_path = os.path.join(root_dir, 'train_img_flod')
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if not os.path.exists(os.path.join(img_crop_path, vedio_name)):
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os.makedirs(os.path.join(img_crop_path, vedio_name))
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cv2.imwrite(os.path.join(img_crop_path, vedio_name, bbox_name[:-4] + '.jpg'), img_crop)
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map_path = os.path.join(map_root, vedio_name, bbox_name[:-9] + 'depth1D.jpg')
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map = cv2.imread(map_path, 0)
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map_crop = cv2.resize(crop_face_from_scene_prnet(map, bbox_path, face_scale), (32, 32))
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map_crop_path = os.path.join(root_dir, 'train_depth_flod')
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if not os.path.exists(os.path.join(map_crop_path, vedio_name)):
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os.makedirs(os.path.join(map_crop_path, vedio_name))
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cv2.imwrite(os.path.join(map_crop_path, vedio_name, bbox_name[:-9] + 'depth1D.jpg'), map_crop)
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