Update utils/image_utils.py

utils/image_utils.py

@@ -1,23 +1,58 @@
-from PIL import Image, ImageDraw, ImageFont
-import base64
-from io import BytesIO
+import numpy as np
+import cv2
+from PIL import Image
+
+def find_low_complexity_row(gray, target_row, search_pct=0.2):
+    """
+    Find a nearby row (within ±20%) that has low edge/text density.
+    """
+    h, w = gray.shape
+    search_radius = int(h * search_pct)
+
+    start = max(0, target_row - search_radius)
+    end   = min(h - 1, target_row + search_radius)
+
+    # Compute edge map
+    edges = cv2.Canny(gray, 80, 160)
+
+    # Sum edges along each row → 1D profile
+    row_scores = edges[start:end].sum(axis=1)
+
+    # Find the row index with the *minimum* score
+    best_local_idx = np.argmin(row_scores)
+
+    # Convert local idx → global row idx
+    best_row = start + best_local_idx
+    return best_row
+
 
 def split_image(image: Image.Image, num_chunks: int) -> list:
+    """
+    Intelligent split: moves split boundaries up/down by ±20% to avoid text.
+    """
     width, height = image.size
-    chunk_height = height // num_chunks
+    img_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    gray = cv2.cvtColor(img_cv, cv2.COLOR_BGR2GRAY)
+
     chunks = []
+    split_points = []
+
+    # First compute approximate "uniform" split points
+    approx_points = [int(i * height / num_chunks) for i in range(1, num_chunks)]
+
+    # Adjust each boundary to a low-density horizontal strip
+    for pt in approx_points:
+        best = find_low_complexity_row(gray, target_row=pt)
+        split_points.append(best)
+
+    # Add start and end
+    split_points = [0] + split_points + [height]
+
+    # Produce chunks
     for i in range(num_chunks):
-        top = i * chunk_height
-        bottom = (i + 1) * chunk_height if i < num_chunks - 1 else height
-        chunks.append(image.crop((0, top, width, bottom)))
-    return chunks
+        top = split_points[i]
+        bottom = split_points[i+1]
+        chunk = image.crop((0, top, width, bottom))
+        chunks.append(chunk)
 
-def encode_image_to_html(image: Image.Image) -> str:
-    buffered = BytesIO()
-    image.save(buffered, format="PNG")
-    encoded = base64.b64encode(buffered.getvalue()).decode()
-    return f"""
-    <div style="height:500px; overflow-y:auto; border:1px solid #ccc;">
-        <img src="data:image/png;base64,{encoded}" style="width:100%;" />
-    </div>
-    """
+    return chunks