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47 changes: 21 additions & 26 deletions paddlex/inference/models/layout_analysis/result.py
Original file line number Diff line number Diff line change
Expand Up @@ -102,23 +102,6 @@ def draw_box(img: Image.Image, boxes: List[dict]) -> Image.Image:


@function_requires_deps("opencv-contrib-python")
def restore_to_draw_masks(img_size, boxes):
"""
Restores extracted masks to the original shape and draws them on a blank image.

"""
restored_masks = []

for i, box_info in enumerate(boxes):
restored_mask = np.zeros(img_size, dtype=np.uint8)
polygon = np.array(box_info["polygon_points"], dtype=np.int32)
polygon = polygon.reshape((-1, 1, 2)) # shape: (N, 1, 2)
cv2.fillPoly(restored_mask, [polygon], 1)
restored_masks.append(restored_mask)

return np.array(restored_masks)


def draw_mask(im, boxes, img_size):
"""
Args:
Expand All @@ -133,21 +116,33 @@ def draw_mask(im, boxes, img_size):
im = np.array(im).astype("float32")
clsid2color = {}

np_masks = restore_to_draw_masks(img_size, boxes)
im_h, im_w = im.shape[:2]
np_masks = np_masks[:, :im_h, :im_w]
mask_h, mask_w = min(img_size[0], im_h), min(img_size[1], im_w)

# draw mask
for i, mask in enumerate(np_masks):
clsid = int(boxes[i]["cls_id"])
# draw mask; rasterize and blend only inside each polygon's bounding box
for i, box_info in enumerate(boxes):
clsid = int(box_info["cls_id"])
if clsid not in clsid2color:
color_index = i % len(color_list)
clsid2color[clsid] = np.array(color_list[color_index])
color_mask = clsid2color[clsid]
idx = np.nonzero(mask)
im[idx[0], idx[1], :] = (1.0 - alpha) * im[
idx[0], idx[1], :
] + alpha * color_mask

polygon = np.array(box_info["polygon_points"], dtype=np.int32).reshape(
(-1, 1, 2)
)
x0 = max(int(polygon[..., 0].min()), 0)
y0 = max(int(polygon[..., 1].min()), 0)
x1 = min(int(polygon[..., 0].max()) + 1, mask_w)
y1 = min(int(polygon[..., 1].max()) + 1, mask_h)
if x0 >= x1 or y0 >= y1:
continue
mask = np.zeros((y1 - y0, x1 - x0), dtype=np.uint8)
cv2.fillPoly(mask, [polygon - np.array([x0, y0], dtype=np.int32)], 1)
region = im[y0:y1, x0:x1]
blended = (1.0 - alpha) * region + alpha * color_mask
np.copyto(
region, blended, casting="same_kind", where=mask.view(bool)[..., None]
)

img = Image.fromarray(np.uint8(im))
font_size = int(0.018 * img.width) + 2
Expand Down
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