sending your input data instances as a JSON object to deployed model about mrcnn_serving_ready

[bendangnuksung]

Hi @jrash33 glad to hear this repo helped you. Coming to your question, there is already an inference RESTAPI code in inferencing/saved_model_inference.py inside there is a method called detect_mask_single_image_using_restapi(). This method sends a requests and gets a JSON response. You can make changes according to your needs.

[bendangnuksung]

Sorry, I do not have any other version that sends requests using a b64 encoded image. The restapi serving model seems to take only list as an input. I do not have any solution as of now but I can tell you two workaround which can help you:

1. (Easy) Make a flask server to work as a medium between your client and serving model. Make GRPC request from your Flask to your serving model as it is much faster.
2. (Hard) Before converting the h5 model, create and attach a training head that accepts image in base64 as part of your model. Then convert your model to serving model. You can look in this AOCR repo which accepts base64 as image, does all the conversion internally inside a model.

Unfortunately, I do not have time to do all this. Do let me know if you find any other way.

[jrash33]

hey @bendangnuksung, wow thank you so much for the reply. Much appreciated. Do you have any versions that can accept b64 encoded images as a single input? I'm trying to pass in images through your method to gcp ai platform and the images seem to be too large. Thanks again!