86 lines
3.0 KiB
Python
86 lines
3.0 KiB
Python
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import cv2
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import numpy as np
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import os
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import random
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from PIL import Image, ImageDraw, ImageFont
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X_RAND_VALUE = 2
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Y_RAND_VALUE = 1
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ROTATE_ANGLE = 3
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BG_COLORS = [
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(33, 40, 45), (36, 51, 62), (35, 37, 154),
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(0, 38, 202), (239, 255, 255), (241, 255, 255)
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]
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DIGIT_COLORS = [(34, 199, 253), (25, 214, 253)]
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def generate_4digit_image():
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bg_color = random.choice(BG_COLORS)
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font_size = random.randint(24, 30)
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font = ImageFont.truetype("arial.ttf", font_size)
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# 扩大画布尺寸(50x160)提供足够缓冲空间
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canvas = np.zeros((50, 160, 3), dtype=np.uint8)
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canvas[:,:] = bg_color
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pil_img = Image.fromarray(canvas)
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draw = ImageDraw.Draw(pil_img)
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digits = []
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for i in range(4):
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digit = str(random.randint(0, 9))
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digits.append(digit)
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x_offset = random.randint(-X_RAND_VALUE, X_RAND_VALUE)
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y_offset = random.randint(-Y_RAND_VALUE, Y_RAND_VALUE)
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digit_color = random.choice(DIGIT_COLORS)
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# 调整数字绘制位置到画布中心区域
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draw.text((20+i*32+x_offset, 12+y_offset), digit,
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font=font, fill=digit_color)
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angle = random.uniform(-ROTATE_ANGLE, ROTATE_ANGLE)
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rotated = pil_img.rotate(angle, expand=True, fillcolor=bg_color)
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# 安全裁剪区域(从扩大后的画布中心裁剪)
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rotated = rotated.crop((20, 10, 148, 42))
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return np.array(rotated), ''.join(digits)
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def generate_train_dataset(num_samples=1000):
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os.makedirs('4digit_train', exist_ok=True)
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with open('4digit_train/labels.csv', 'w') as f:
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f.write(f"filename,words\n")
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for i in range(num_samples):
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img, label = generate_4digit_image()
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# print(f"type of label : {type(label)}")
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label = str(label).zfill(4)
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img_path = f'4digit_train/{i:04d}.jpg'
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cv2.imwrite(img_path, img)
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f.write(f"{i:04d}.jpg,{label}\n")
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def generate_valid_dataset(num_samples=200):
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os.makedirs('4digit_valid', exist_ok=True)
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with open('4digit_valid/labels.csv', 'w') as f:
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f.write(f"filename,words\n")
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for i in range(num_samples):
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img, label = generate_4digit_image()
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label = str(label).zfill(4)
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img_path = f'4digit_valid/{i:04d}.jpg'
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cv2.imwrite(img_path, img)
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f.write(f"{i:04d}.jpg,{label}\n")
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def generate_eval_dataset(num_samples=200):
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os.makedirs('4digit_eval', exist_ok=True)
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with open('4digit_eval/labels.csv', 'w') as f:
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f.write(f"filename,words\n")
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for i in range(num_samples):
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img, label = generate_4digit_image()
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label = str(label).zfill(4)
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img_path = f'4digit_eval/{i:04d}.jpg'
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cv2.imwrite(img_path, img)
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f.write(f"{i:04d}.jpg,{label}\n")
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if __name__ == "__main__":
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generate_train_dataset()
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generate_eval_dataset()
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generate_valid_dataset() |