Asking for predictions Sample Clauses

Asking for predictions. The process uses the deployed model to analyse the image frames obtained on the previous steps and tagging the objects detected on each of them. This step is recommended to be run in parallel to obtain a better speedup on the tagging and image processing job. An example of such code is shown in Figure 9. # Start detection for each image for file_name in imagesList: img = cv2.xxxxxx(file_name) output_dict = run_inference_for_single_image( np.expand_dims(img, axis=0), sess, tensor_dict, detection_masks, detection_boxes, ) # Draw boxes vis_util.visualize_boxes_and_labels_on_image_array( img, output_dict["detection_boxes"], output_dict["detection_classes"], output_dict["detection_scores"], category_index, instance_masks=output_dict.get("detection_masks"), use_normalized_coordinates=True, line_thickness=8, ) # Save tagged image _, name = os.path.split(file_name) name, ext = os.path.splitext(name) tagged_image = f"{output_dir}/{name}_tagged{ext}" cv2.imwrite(tagged_image, img) Figure 9. Example Python code to start the object detection on each frame Table 7. Computational Requirements for Asking for predictions step
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