![]() ![]() The following function is necessary to get a sequence of the contours and to sort them from top-to-bottom ( ). # Detect contours for following box detection contours, hierarchy = cv2.findContours(img_vh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) This helps us to retrieve the exact coordinates of each box. The extracted tabular structure without cotaining text.Īfter having the tabular structure we use the findContours function to detect the contours. #Use vertical kernel to detect and save the vertical lines in a jpg image_1 = cv2.erode(img_bin, ver_kernel, iterations=3) vertical_lines = cv2.dilate(image_1, ver_kernel, iterations=3) cv2.imwrite("/Users/YOURPATH/vertical.jpg",vertical_lines) #Plot the generated image plotting = plt.imshow(image_1,cmap='gray') plt.show() The next step is the detection of the vertical lines. # Length(width) of kernel as 100th of total width kernel_len = np.array(img).shape//100 # Defining a vertical kernel to detect all vertical lines of image ver_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, kernel_len)) # Defining a horizontal kernel to detect all horizontal lines of image hor_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (kernel_len, 1)) # A kernel of 2x2 kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2)) First, we define the length of the kernel and following the vertical and horizontal kernels to detect later on all vertical lines and all horizontal lines. The next step is to define a kernel to detect rectangular boxes, and followingly the tabular structure. ![]() However, what if your PDF is image-based or if you find an article with a table online? Why not just take a screenshot and convert it into an excel sheet? Since there seems to be no free or open source software for image-based data (jpg, png, image-based pdf etc.) the idea came up to develop a generic solution to convert tables into editable excel-files.īut that’s enough for now, let’s see how it works. The most popular ones are tabular, camelot/excalibur, which you can find under,. In the case that your data exists of text-based PDFs there is already a handful of free solutions. Especially in the field of preprocessing for Machine Learning this algorithm will be exceptionally helpful to convert many images and tables to editable data. Let’s say you have a table in an article, pdf or image and want to transfer it into an excel sheet or dataframe to have the possibility to edit it. ![]()
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