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@ -140,22 +140,21 @@ def draw_ocr(image, boxes, txts, scores, draw_txt=True, drop_score=0.5):
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return(array):
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return(array):
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the visualized img
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the visualized img
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"""
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"""
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img = image
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if scores is None:
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if scores is None:
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scores = [1] * len(boxes)
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scores = [1] * len(boxes)
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for (box, score) in zip(boxes, scores):
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for (box, score) in zip(boxes, scores):
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if score < drop_score or math.isnan(score):
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if score < drop_score or math.isnan(score):
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continue
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continue
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box = np.reshape(np.array(box), [-1, 1, 2]).astype(np.int64)
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box = np.reshape(np.array(box), [-1, 1, 2]).astype(np.int64)
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img = cv2.polylines(np.array(image), [box], True, (255, 0, 0), 3)
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image = cv2.polylines(np.array(image), [box], True, (255, 0, 0), 2)
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if draw_txt:
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if draw_txt:
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img = np.array(resize_img(img, input_size=600))
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img = np.array(resize_img(image, input_size=600))
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txt_img = text_visual(
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txt_img = text_visual(
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txts, scores, img_h=img.shape[0], img_w=600, threshold=drop_score)
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txts, scores, img_h=img.shape[0], img_w=600, threshold=drop_score)
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img = np.concatenate([np.array(img), np.array(txt_img)], axis=1)
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img = np.concatenate([np.array(img), np.array(txt_img)], axis=1)
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return img
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return img
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return image
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def str_count(s):
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def str_count(s):
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@ -213,7 +212,7 @@ def text_visual(texts, scores, img_h=400, img_w=600, threshold=0.):
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gap = font_size + 5
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gap = font_size + 5
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txt_img_list = []
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txt_img_list = []
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count, index = 0, 0
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count, index = 1, 0
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for idx, txt in enumerate(texts):
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for idx, txt in enumerate(texts):
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index += 1
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index += 1
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if scores[idx] < threshold or math.isnan(scores[idx]):
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if scores[idx] < threshold or math.isnan(scores[idx]):
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@ -230,24 +229,22 @@ def text_visual(texts, scores, img_h=400, img_w=600, threshold=0.):
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new_txt = ' ' + txt
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new_txt = ' ' + txt
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draw_txt.text((0, gap * (count + 1)), new_txt, txt_color, font=font)
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draw_txt.text((0, gap * (count + 1)), new_txt, txt_color, font=font)
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txt = tmp[img_w // font_size - 4:]
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txt = tmp[img_w // font_size - 4:]
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count += 1
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if count >= img_h // gap - 1:
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if count >= img_h // gap - 1:
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txt_img_list.append(np.array(blank_img))
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txt_img_list.append(np.array(blank_img))
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blank_img, draw_txt = create_blank_img()
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blank_img, draw_txt = create_blank_img()
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count = 0
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count = 0
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count += 1
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if first_line:
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if first_line:
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new_txt = str(index) + ': ' + txt + ' ' + '%.3f' % (scores[idx])
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new_txt = str(index) + ': ' + txt + ' ' + '%.3f' % (scores[idx])
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else:
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else:
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new_txt = " " + txt + " " + '%.3f' % (scores[idx])
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new_txt = " " + txt + " " + '%.3f' % (scores[idx])
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draw_txt.text((0, gap * (count + 1)), new_txt, txt_color, font=font)
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draw_txt.text((0, gap * count), new_txt, txt_color, font=font)
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count += 1
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# whether add new blank img or not
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# whether add new blank img or not
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if count > img_h // gap - 1 and idx + 1 < len(texts):
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if count >= img_h // gap - 1 and idx + 1 < len(texts):
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txt_img_list.append(np.array(blank_img))
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txt_img_list.append(np.array(blank_img))
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blank_img, draw_txt = create_blank_img()
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blank_img, draw_txt = create_blank_img()
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count = 0
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count = 0
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count += 1
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txt_img_list.append(np.array(blank_img))
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txt_img_list.append(np.array(blank_img))
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if len(txt_img_list) == 1:
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if len(txt_img_list) == 1:
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blank_img = np.array(txt_img_list[0])
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blank_img = np.array(txt_img_list[0])
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@ -275,4 +272,4 @@ if __name__ == '__main__':
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new_img = draw_ocr(image, boxes, txts, scores, draw_txt=True)
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new_img = draw_ocr(image, boxes, txts, scores, draw_txt=True)
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cv2.imwrite(img_name, new_img)
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cv2.imwrite(img_name, new_img)
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