8000 Fix colors in OCR slicing by VikParuchuri · Pull Request #111 · datalab-to/surya · GitHub
[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to content

Fix colors in OCR slicing #111

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
May 23, 2024
Merged

Fix colors in OCR slicing #111

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 3 additions & 2 deletions surya/input/processing.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -81,7 +81,7 @@ def slice_bboxes_from_image(image: Image.Image, bboxes):


def slice_polys_from_image(image: Image.Image, polys):
image_array = np.array(image)
image_array = np.array(image, dtype=np.uint8)
lines = []
for idx, poly in enumerate(polys):
lines.append(slice_and_pad_poly(image_array, poly))
Expand All @@ -98,8 +98,9 @@ def slice_and_pad_poly(image_array: np.array, coordinates):
coordinates = [(x - bbox[0], y - bbox[1]) for x, y in coordinates]

# Pad the area outside the polygon with the pad value
mask = np.zeros_like(cropped_polygon, dtype=np.uint8)
mask = np.zeros(cropped_polygon.shape[:2], dtype=np.uint8)
cv2.fillPoly(mask, [np.int32(coordinates)], 1)
mask = np.stack([mask] * 3, axis=-1)

cropped_polygon[mask == 0] = settings.RECOGNITION_PAD_VALUE
rectangle_image = Image.fromarray(cropped_polygon)
Expand Down
2 changes: 1 addition & 1 deletion surya/model/recognition/processor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -155,7 +155,7 @@ def align_long_axis(
data_format: Optional[Union[str, ChannelDimension]] = None,
input_data_format: Optional[Union[str, ChannelDimension]] = None,
) -> np.ndarray:
input_height, input_width = get_image_size(image, channel_dim=input_data_format)
input_height, input_width = image.shape[:2]
output_height, output_width = size["height"], size["width"]

if (output_width < output_height and input_width > input_height) or (
Expand Down
1 change: 1 addition & 0 deletions surya/ocr.py
View file
Open in desktop
B939
Original file line number Diff line number Diff line change
Expand Up @@ -62,6 +62,7 @@ def run_ocr(images: List[Image.Image], langs: List[List[str]], det_model, det_pr
all_slices = []
slice_map = []
all_langs = []

for idx, (det_pred, image, lang) in enumerate(zip(det_predictions, images, langs)):
polygons = [p.polygon for p in det_pred.bboxes]
slices = slice_polys_from_image(image, polygons)
Expand Down
1 change: 1 addition & 0 deletions surya/recognition.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -37,6 +37,7 @@ def batch_recognition(images: List, languages: List[List[str]], model, processor
has_math = ["_math" in lang for lang in batch_langs]
batch_images = images[i:i+batch_size]
batch_images = [image.convert("RGB") for image in batch_images]

model_inputs = processor(text=[""] * len(batch_langs), images=batch_images, lang=batch_langs)

batch_pixel_values = model_inputs["pixel_values"]
Expand Down
Loading
0