Inpaint | Examplar Inpainting using OpenCV | Computer Vision library

As ifelse is vectorized we can move that outside of for loop to get some improvements:

Here is the best solution I could come up with, still open to others with more experience showing me a better way if anyone has an idea.

If all your images are like this and have a watermark as shown in the question having a light gray watermark then a simple thresholding operation will work.

You are accessing the tensor's .shape property which gives you Dimension objects and not actually the shape values. You have 2 options:

1. If you know the shape and it's fixed at layer creation time you can use K.int_shape(x)[0] which will give the value as an integer. It will however return None if the shape is unknown at creation time; for example if the batch_size is unknown.
2. If shape will be determined at runtime then you can use K.shape(x)[0] which will return a symbolic tensor that will hold the shape value at runtime.

Mainly, dilate the mask used for the inpainting. Also, enlarging the inpaint radius will give slightly better results.

That'd be my suggestion:

It's rather hard to help you because you haven't provided a Minimum Complete Verifiable Example of your code with all the import statements and code showing how you open your images, or even indicated whether you are using OpenCV or PIL or skimage. Also, you haven't provided the second file with the mask of all the points that need in-painting, nor do I know what you are actually trying to achieve, so for the moment, I am just trying to provide a method that looks to me like it gets a similar result to the one you show.

Anyway, here's a method that uses morphology and takes 100 microseconds on my Mac - which may not be anything like whatever you are using ;-)

I've try many ways and my final thought is that pre trained keras models are not compatible. I changed it to a tensorflow VGG16 model and it works slower but at least it works.

It's the slice operator being applied to the lists, it just looks odd because of the long names, and because there's a space after the colon. If you simplify a bit, it's just:

This exception happens whenever an orchestrator function does async work in an unsupported way. "Unsupported" in this context effectively means that await was used on a non-durable task (and "non-durable" means that it was a task that came from some API other than DurableOrchestrationContext).

You can find more information on the code constraints for orchestrator functions here: https://docs.microsoft.com/en-us/azure/azure-functions/durable/durable-functions-checkpointing-and-replay#orchestrator-code-constraints.

Here are the rules that were broken in your code when I quickly scanned it:

• Orchestrator code should be non-blocking. For example, that means no I/O and no calls to Thread.Sleep or equivalent APIs. If an orchestrator needs to delay, it can use the CreateTimer API.

• Orchestrator code must never initiate any async operation except by using the DurableOrchestrationContext API. For example, no Task.Run, Task.Delay or HttpClient.SendAsync. The Durable Task Framework executes orchestrator code on a single thread and cannot interact with any other threads that could be scheduled by other async APIs.

This exception specifically occurs when we detect that an unsupported async call is made. I noticed that is happening in this code: