bachpc commited on
Commit
87f7012
1 Parent(s): ba538d2
Files changed (1) hide show
  1. app.py +10 -8
app.py CHANGED
@@ -193,7 +193,7 @@ def visualize_structure(pil_img, structure_result):
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  y2 = int((min_y + h / 2) * height)
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  # print(x1, y1, x2, y2)
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- if score >= structure_class_map[structure_class_names[class_id]]:
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  cv2.rectangle(image, (x1, y1), (x2, y2), color=(0, 0, 255))
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  #cv2.putText(image, str(i)+'-'+str(class_id), (x1-10, y1), cv2.FONT_HERSHEY_SIMPLEX, fontScale=1, color=(0,0,255))
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@@ -387,18 +387,18 @@ def main():
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  else:
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  print(filename)
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  pil_img = PIL.Image.open(filename)
 
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  detection_result = table_detection(pil_img)
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  crop_images, vis_det_img = crop_image(pil_img, detection_result)
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- cols[0].image(vis_det_img)
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- str_cols = st.columns((len(crop_images), ) * 6)
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  str_cols[0].subheader("Table image")
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  str_cols[1].subheader("OCR result")
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  str_cols[2].subheader("Structure result")
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  str_cols[3].subheader("Cells result")
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- str_cols[4].subheader("HTML result")
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- str_cols[5].subheader("CSV result")
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  for img in crop_images:
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  ocr_result = ocr(img)
@@ -407,6 +407,7 @@ def main():
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  cells = extract_text_from_cells(cells)
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  html_result = cells_to_html(cells)
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  df, csv_result = cells_to_csv(cells)
 
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  vis_ocr_img = visualize_ocr(img, ocr_result)
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  vis_str_img = visualize_structure(img, structure_result)
@@ -416,9 +417,10 @@ def main():
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  str_cols[1].image(vis_ocr_img)
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  str_cols[2].image(vis_str_img)
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  str_cols[3].image(vis_cells_img)
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- str_cols[4].markdown(html_result, unsafe_allow_html=True)
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- str_cols[5].dataframe(df)
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- str_cols[5].download_button("Download table", csv_result, "file.csv", "text/csv", key='download-csv')
 
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  if __name__ == '__main__':
 
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  y2 = int((min_y + h / 2) * height)
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  # print(x1, y1, x2, y2)
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+ if score >= structure_class_thresholds[structure_class_names[class_id]]:
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  cv2.rectangle(image, (x1, y1), (x2, y2), color=(0, 0, 255))
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  #cv2.putText(image, str(i)+'-'+str(class_id), (x1-10, y1), cv2.FONT_HERSHEY_SIMPLEX, fontScale=1, color=(0,0,255))
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  else:
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  print(filename)
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  pil_img = PIL.Image.open(filename)
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+ cols[0].image(pil_img)
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  detection_result = table_detection(pil_img)
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  crop_images, vis_det_img = crop_image(pil_img, detection_result)
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+ cols[1].image(vis_det_img)
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+ str_cols = st.columns((len(crop_images), ) * 5)
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  str_cols[0].subheader("Table image")
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  str_cols[1].subheader("OCR result")
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  str_cols[2].subheader("Structure result")
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  str_cols[3].subheader("Cells result")
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+ str_cols[4].subheader("CSV result")
 
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  for img in crop_images:
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  ocr_result = ocr(img)
 
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  cells = extract_text_from_cells(cells)
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  html_result = cells_to_html(cells)
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  df, csv_result = cells_to_csv(cells)
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+ print(df)
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  vis_ocr_img = visualize_ocr(img, ocr_result)
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  vis_str_img = visualize_structure(img, structure_result)
 
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  str_cols[1].image(vis_ocr_img)
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  str_cols[2].image(vis_str_img)
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  str_cols[3].image(vis_cells_img)
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+ #str_cols[4].dataframe(df)
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+ str_cols[4].download_button("Download table", csv_result, "file.csv", "text/csv", key='download-csv')
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+
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+ st.markdown(html_result, unsafe_allow_html=True)
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  if __name__ == '__main__':