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from mmocr.ocr import MMOCR | |
import gradio as gr | |
import cv2 | |
model_dir = 'model' | |
ocr = MMOCR(det_config=f'{model_dir}/config.py', | |
det_ckpt=f'{model_dir}/epoch_40.pth', device='cpu') | |
def get_rec(points): | |
xs = [] | |
ys = [] | |
for ix, iv in enumerate(points): | |
if ix % 2: | |
ys.append(iv) | |
else: | |
xs.append(iv) | |
return (min(xs), min(ys)), (max(xs), max(ys)) | |
def predict(image_input): | |
draw_img = image_input.copy() | |
output = ocr.readtext(image_input) | |
for polygon in output['det_polygons']: | |
p0, p1 = get_rec([int(i) for i in polygon]) | |
draw_img = cv2.rectangle(draw_img, p0, p1, (255,255,255)) | |
return draw_img | |
def run(): | |
demo = gr.Interface( | |
fn=predict, | |
inputs=gr.components.Image(), | |
outputs=gr.components.Image(), | |
) | |
demo.launch(server_name="0.0.0.0", server_port=7860) | |
if __name__ == "__main__": | |
run() |