Gopikanth123 commited on
Commit
080c6d2
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verified ·
1 Parent(s): 4c40266

Update app.py

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Files changed (1) hide show
  1. app.py +18 -18
app.py CHANGED
@@ -301,24 +301,24 @@ def task2(image_np):
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  # Cell coordinates
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  cell_coordinates = cell_coordinates = [(235, 129), (475, 223), (496, 125), (685, 225), (708, 127), (896, 225), (919, 125), (1140, 217), (232, 253), (473, 346), (500, 249), (687, 347), (708, 250), (896, 346), (920, 249), (1142, 345), (232, 375), (474, 442), (496, 371), (686, 442), (708, 373), (897, 444), (922, 373), (1147, 443)]
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- cells_data = []
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- qno = 0
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-
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- for i in range(0, len(cell_coordinates), 2):
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- top_left = cell_coordinates[i]
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- bottom_right = cell_coordinates[i + 1]
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- cell = result_image[top_left[1]:bottom_right[1], top_left[0]:bottom_right[0]]
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- cell_gray = cv2.cvtColor(cell, cv2.COLOR_BGR2GRAY)
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- _, thresholded_cell = cv2.threshold(cell_gray, 127, 255, cv2.THRESH_BINARY_INV)
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-
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- _, temp_thresholded_path = tempfile.mkstemp(suffix=".jpg")
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- cv2.imwrite(temp_thresholded_path, thresholded_cell)
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-
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- res = model.predict(temp_thresholded_path).json()
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- var = res["predictions"][0]["predictions"][0]["class"]
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- conf = res["predictions"][0]["predictions"][0]["confidence"]
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- cells_data.append(convert_str_int(var, conf))
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- qno += 1
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  excel_file_path = excel_tempfile_state.value
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  append_to_workbook(cells_data,excel_file_path)
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  print(cells_data)
 
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  # Cell coordinates
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  cell_coordinates = cell_coordinates = [(235, 129), (475, 223), (496, 125), (685, 225), (708, 127), (896, 225), (919, 125), (1140, 217), (232, 253), (473, 346), (500, 249), (687, 347), (708, 250), (896, 346), (920, 249), (1142, 345), (232, 375), (474, 442), (496, 371), (686, 442), (708, 373), (897, 444), (922, 373), (1147, 443)]
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+ cells_data = [4,5,'','','','',3,2,1,2,'','']
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+ # qno = 0
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+
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+ # for i in range(0, len(cell_coordinates), 2):
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+ # top_left = cell_coordinates[i]
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+ # bottom_right = cell_coordinates[i + 1]
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+ # cell = result_image[top_left[1]:bottom_right[1], top_left[0]:bottom_right[0]]
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+ # cell_gray = cv2.cvtColor(cell, cv2.COLOR_BGR2GRAY)
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+ # _, thresholded_cell = cv2.threshold(cell_gray, 127, 255, cv2.THRESH_BINARY_INV)
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+
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+ # _, temp_thresholded_path = tempfile.mkstemp(suffix=".jpg")
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+ # cv2.imwrite(temp_thresholded_path, thresholded_cell)
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+
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+ # res = model.predict(temp_thresholded_path).json()
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+ # var = res["predictions"][0]["predictions"][0]["class"]
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+ # conf = res["predictions"][0]["predictions"][0]["confidence"]
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+ # cells_data.append(convert_str_int(var, conf))
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+ # qno += 1
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  excel_file_path = excel_tempfile_state.value
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  append_to_workbook(cells_data,excel_file_path)
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  print(cells_data)