[MYAI Studio SDK] Image-Object-Detection-FasterRCNN-Keras-Jupyter

Use FasterRCNN for object detection, which can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, and mask image analysis.


The solution process is:

Annotate images -> training -> inference

1. 1_annotation_pascal_voc_xml.ipynb

After running, open the web page for image annotation.


In # parameters, --port 8801 is the port occupied by the webpage. If the user 8801 is occupied, please change the port value by yourself.

2. 2_delete_log.ipynb

Delete the log folder.

3. 3_train.ipynb

Start training.

If you don't use the tensorboard , you can skip points 2, 4, and 5.

4. 4_kill_tensorboard.ipynb

Before using tensorboard to see the loss value, close tensorboard first.

5. 5_tensorboard.ipynb

During training, you can run 4 and 5 points to see the training status, but you must execute 2_delete_log.ipynb before training.

6. 6_inference.ipynb

Inferring a single image.


-p is the path to infer the image.


This SDK is built in AppForAI - AI Dev Tools.

Purchase license separately: USD 600, permanent authorization, single APP authorization, single machine authorization, one-year activation, one-year download, one-year update, one-year email technical support.

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