Day #241 - Tensorflow on CPU - Object Detection

Finally was able to train Custom Object Detection

Notes on Custom Object Detection (Notes - Link )
Step #1 - Define Inputs - Specify files in TFRecord file format
Step #2 - Configure Train_config. Key Values are

• Model parameter initialization.
• Input preprocessing.
• SGD parameters.

Step #3 - fine_tune_checkpoint should provide a path to the pre-existing checkpoint, To speed up the training process, it is recommended that users re-use the feature extractor parameters from a pre-existing image classification or object detection checkpoint
Step #4 - SGD - hyperparameters for gradient descent
Step #5 - Evaluator Config)

To get reasonable mAP@IoU scores for object detection API:

1. Try varying the Intersection over Union (IoU) threshold, e.g 0.2-0.5 and see if you get an increase in average precision. You would have to modify matching_iou_threshold parameter in object_detection/utils/object_detection_evaluation.py

2. Try different evaluator classes (the default one is EVAL_DEFAULT_METRIC = 'pascal_voc_detection_metrics'). If you are training on Open Image Dataset it makes sense to use open_images_V2_detection_metrics

3. Check your eval config file and increase the number of examples used in the evaluation set, e.g.

eval_config: {
  num_examples: 20000
  num_visualizations: 16
  min_score_threshold: 0.2
  # Note: The below line limits the evaluation process to 10 evaluations.
  # Remove the below line to evaluate indefinitely.
  max_evals: 1
}

4. Train the object detector for more iterations
5. Check current mAP against reported metrics (e.g. COCO mAP@IoU=0.5)

Step by Step: Build Your Custom Real-Time Object Detector  - Link
Detectron2 Train a Instance Segmentation Model
Installing the Tensorflow Object Detection API

For custom object training BMW has shared their opensource framework. It is a packaged version of the complete object detection setup. (Yolo / TensorFlow this is good set of tools)

https://github.com/BMW-InnovationLab

I haven't experimented with it. This is a good place to leverage the setup as common tool.  This was released few months back. I am working in my windows setup for a while.

Happy Mastering DL!!!