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import os
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import json
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import cv2
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import numpy as np
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input_label_file = "D:/MyCode/Python/Model/paddleocr/total_text/test/test.txt"
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image_root = "D:/MyCode/Python/Model/paddleocr/total_text/test"
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output_label_file = "D:/MyCode/Python/Model/paddleocr/total_text/test/test_rec.txt"
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crop_output_dir = os.path.join(image_root, "rec_crop")
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os.makedirs(crop_output_dir, exist_ok=True)
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with open(input_label_file, "r", encoding="utf-8") as f:
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lines = f.readlines()
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out_lines = []
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crop_id = 0
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for line in lines:
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img_path_rel, anns = line.strip().split('\t')
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img_path = os.path.join(image_root, img_path_rel)
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anns = json.loads(anns)
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if not os.path.exists(img_path):
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print(f"[WARNING] Không tìm thấy ảnh: {img_path}")
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continue
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img = cv2.imread(img_path)
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if img is None:
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print(f"[WARNING] Lỗi đọc ảnh: {img_path}")
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continue
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height, width = img.shape[:2]
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for ann in anns:
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text = ann['transcription']
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points = ann['points']
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if text.strip().lower() == "###" or not text.strip():
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continue
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pts = np.array(points, dtype="float32")
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x, y, w, h = cv2.boundingRect(pts.astype("int"))
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x = max(0, x)
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y = max(0, y)
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if x + w > width or y + h > height:
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print(f"[WARNING] Box vượt quá kích thước ảnh ({img_path}): x={x}, y={y}, w={w}, h={h}")
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continue
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cropped = img[y:y+h, x:x+w]
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if cropped is None or cropped.size == 0:
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print(f"[WARNING] Ảnh crop rỗng ({img_path}), bỏ qua.")
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continue
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crop_img_name = f"{os.path.splitext(os.path.basename(img_path))[0]}_crop_{crop_id}.jpg"
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crop_img_path = os.path.join(crop_output_dir, crop_img_name)
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cv2.imwrite(crop_img_path, cropped)
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out_line = f"rec_crop/{crop_img_name}\t{text.strip()}"
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out_lines.append(out_line)
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crop_id += 1
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with open(output_label_file, "w", encoding="utf-8") as f:
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f.write('\n'.join(out_lines))
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print(f"✅ Đã tạo {len(out_lines)} mẫu recognition tại: {output_label_file}")
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