src/dataset-generator/create_dataset_from_raw_csv.py [127:169]:
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            in_file_color_reg = find_file_in_dirs(source_dirs, im_basename + '_COLOR-8-BIT.JPG')
            # If we have all input files for registration
            if os.path.isfile(out_file_ir_reg):
                print('Registered IR image for {} already exists, skipping...'.format(im_basename))
            elif find_file_in_dirs(source_dirs, os.path.basename(out_file_ir_reg)):
                print('Registered IR image for {} exists in the source directories, copying...'.format(im_basename))
                shutil.copy(find_file_in_dirs(source_dirs, os.path.basename(out_file_ir_reg)), output_dir)
            elif in_file_ir_reg and in_file_color_reg:
                # Read input images
                image_ir_n = imreadIR(in_file_ir_reg)[0]
                image_to_warp = imreadIR(out_file_n)[1]
                image_color = cv2.imread(in_file_color_reg)
                # compute transform
                ret, transform, inliers = computeTransform(image_color, image_ir_n)
                if ret:
                    # Check if transform is good using IR and color image anntoations
                    all_close = True
                    for _, x in rel_ann.iterrows():
                        warped_ir_hotspot = np.array(warpPoint([x.x_pos, x.y_pos], transform))
                        color_hotspot = np.array([x.object_centers_x, x.object_centers_y])
                        warping_error = np.linalg.norm(warped_ir_hotspot - color_hotspot)
                        all_close = all_close and warping_error < reg_rejection_thr * object_width
                    # Save warped image if successful
                    if all_close:
                        image_warped = cv2.warpPerspective(image_to_warp, transform, (image_color.shape[1], image_color.shape[0]))
                        #cv2.imwrite(out_file_ir_reg, image_warped)
                        with open(out_file_ir_reg, 'wb') as f:
                            writer = png.Writer(width=image_warped.shape[1],
                                    height=image_warped.shape[0],
                                    bitdepth=16,
                                    greyscale=True)
                            pixel_list = image_warped.tolist()
                            writer.write(f, pixel_list)
                    else:
                        print('Registration is too inaccurate, skipping this image.')
                else:
                    print("Failed to register {}".format(im_basename))
            else:
                print('Couldn\'t find color and IR images for {} for registration.'.format(im_basename))

        # Copy all images related to *im_basename* to *output_dir*
        for source_dir in source_dirs:
            for tag in tags:
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src/dataset-generator/create_dataset_from_updated_csv.py [125:167]:
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            in_file_color_reg = find_file_in_dirs(source_dirs, im_basename + '_COLOR-8-BIT.JPG')
            # If we have all input files for registration
            if os.path.isfile(out_file_ir_reg):
                print('Registered IR image for {} already exists, skipping...'.format(im_basename))
            elif find_file_in_dirs(source_dirs, os.path.basename(out_file_ir_reg)):
                print('Registered IR image for {} exists in the source directories, copying...'.format(im_basename))
                shutil.copy(find_file_in_dirs(source_dirs, os.path.basename(out_file_ir_reg)), output_dir)
            elif in_file_ir_reg and in_file_color_reg:
                # Read input images
                image_ir_n = imreadIR(in_file_ir_reg)[0]
                image_to_warp = imreadIR(out_file_n)[1]
                image_color = cv2.imread(in_file_color_reg)
                # compute transform
                ret, transform, inliers = computeTransform(image_color, image_ir_n)
                if ret:
                    # Check if transform is good using IR and color image anntoations
                    all_close = True
                    for _, x in rel_ann.iterrows():
                        warped_ir_hotspot = np.array(warpPoint([x.x_pos, x.y_pos], transform))
                        color_hotspot = np.array([x.object_centers_x, x.object_centers_y])
                        warping_error = np.linalg.norm(warped_ir_hotspot - color_hotspot)
                        all_close = all_close and warping_error < reg_rejection_thr * object_width
                    # Save warped image if successful
                    if all_close:
                        image_warped = cv2.warpPerspective(image_to_warp, transform, (image_color.shape[1], image_color.shape[0]))
                        #cv2.imwrite(out_file_ir_reg, image_warped)
                        with open(out_file_ir_reg, 'wb') as f:
                            writer = png.Writer(width=image_warped.shape[1],
                                    height=image_warped.shape[0],
                                    bitdepth=16,
                                    greyscale=True)
                            pixel_list = image_warped.tolist()
                            writer.write(f, pixel_list)
                    else:
                        print('Registration is too inaccurate, skipping this image.')
                else:
                    print("Failed to register {}".format(im_basename))
            else:
                print('Couldn\'t find color and IR images for {} for registration.'.format(im_basename))

        # Copy all images related to *im_basename* to *output_dir*
        for source_dir in source_dirs:
            for tag in tags:
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