training and synthetic data generation code

manga_ocr_dev/data/generate_backgrounds.py

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+from pathlib import Path
+
+import cv2
+import numpy as np
+import pandas as pd
+from tqdm import tqdm
+
+from manga_ocr_dev.env import MANGA109_ROOT, BACKGROUND_DIR
+
+
+def find_rectangle(mask, y, x, aspect_ratio_range=(0.33, 3.0)):
+    ymin_ = ymax_ = y
+    xmin_ = xmax_ = x
+
+    ymin = ymax = xmin = xmax = None
+
+    while True:
+        if ymin is None:
+            ymin_ -= 1
+            if ymin_ == 0 or mask[ymin_, xmin_:xmax_].any():
+                ymin = ymin_
+
+        if ymax is None:
+            ymax_ += 1
+            if ymax_ == mask.shape[0] - 1 or mask[ymax_, xmin_:xmax_].any():
+                ymax = ymax_
+
+        if xmin is None:
+            xmin_ -= 1
+            if xmin_ == 0 or mask[ymin_:ymax_, xmin_].any():
+                xmin = xmin_
+
+        if xmax is None:
+            xmax_ += 1
+            if xmax_ == mask.shape[1] - 1 or mask[ymin_:ymax_, xmax_].any():
+                xmax = xmax_
+
+        h = ymax_ - ymin_
+        w = xmax_ - xmin_
+        if h > 1 and w > 1:
+            ratio = w / h
+            if ratio < aspect_ratio_range[0] or ratio > aspect_ratio_range[1]:
+                return ymin_, ymax_, xmin_, xmax_
+
+        if None not in (ymin, ymax, xmin, xmax):
+            return ymin, ymax, xmin, xmax
+
+
+def generate_backgrounds(crops_per_page=5, min_size=40):
+    data = pd.read_csv(MANGA109_ROOT / 'data.csv')
+    frames_df = pd.read_csv(MANGA109_ROOT / 'frames.csv')
+
+    BACKGROUND_DIR.mkdir(parents=True, exist_ok=True)
+
+    page_paths = data.page_path.unique()
+    for page_path in tqdm(page_paths):
+        page = cv2.imread(str(MANGA109_ROOT / page_path))
+        mask = np.zeros((page.shape[0], page.shape[1]), dtype=bool)
+        for row in data[data.page_path == page_path].itertuples():
+            mask[row.ymin:row.ymax, row.xmin:row.xmax] = True
+
+        frames_mask = np.zeros((page.shape[0], page.shape[1]), dtype=bool)
+        for row in frames_df[frames_df.page_path == page_path].itertuples():
+            frames_mask[row.ymin:row.ymax, row.xmin:row.xmax] = True
+
+        mask = mask | ~frames_mask
+
+        if mask.all():
+            continue
+
+        unmasked_points = np.stack(np.where(~mask), axis=1)
+        for i in range(crops_per_page):
+            p = unmasked_points[np.random.randint(0, unmasked_points.shape[0])]
+            y, x = p
+            ymin, ymax, xmin, xmax = find_rectangle(mask, y, x)
+            crop = page[ymin:ymax, xmin:xmax]
+
+            if crop.shape[0] >= min_size and crop.shape[1] >= min_size:
+                out_filename = '_'.join(
+                    Path(page_path).with_suffix('').parts[-2:]) + f'_{ymin}_{ymax}_{xmin}_{xmax}.png'
+                cv2.imwrite(str(BACKGROUND_DIR / out_filename), crop)
+
+
+if __name__ == '__main__':
+    generate_backgrounds()