REST API - Send Images to PEKAT
Image processing through API works on the principle of sending the image via HTTP request and getting a response with the result (contains Context by default, but there are also other response types available). Only one image can be sent per request.
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Enable Process
The user must enable Process on the left of the panel in the Camera tab to be able to process the image sent through API.
Request
The sending address consists of the IP address, port, type, and optional further query parameters. The request method must be of โPOSTโ type and the content type of โapplication/octet-streamโ type.
Find a practical API demonstration in Python atย
IP Address
If the project runs on a local computer, the address is 127.0.0.1. If a remote computer is accessed, then you need to use the IP address of the remote computer.
It is necessary to specify the IP address of the PC that is going to send the images. To do this navigate to Input โ Host panel and modify the IP address.
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Port
This is selected when starting the project, the default is 8000.
Data
You can add extra information to the request. This string will be added to the context (the key is data). It is available only in the Code module (context variable).
'http://127.0.0.1:8000/analyze_image?data=SomeInfo'
In the Code module, you can access this string using:
context['data']
Types
analyze_raw_image
Used for sending the image as raw data. For example, the NumPy array in Python is converted to binary format.
You need to send the image dimensions in query parameters width and height.
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Example of a 1920x1024 image:
'http://127.0.0.1:8000/analyze_raw_image?width=1920&height=1024'
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If you are sending Bayer RG 8 data, it is necessary to add an argumentย bayer.
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Example of a Python code sending requests with raw images from the camera:
analyze_image
Is used for sending an image in โjpgโ or โpngโ formats.
Basic example
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Example Python code that sends images from a folder to the Pekat project with an API key:
last_image
Gets the last image/context that was analyzed in the given project before.
Basic example (gets just the context)
Python code which gets the last processed image with heatmap and shows it then prints out the context.
Response type
Query parameter โresponse_typeโ determines what content will be sent in the response that is returned from PEKAT VISION after processing the request. The request URL changes in the following way (example for annotated_image response type):
Context
context โ a serialized context in JSON format. The contents are explained on the Context page. You can access the context json from the response using:
Images
Further options return a PNG image in binary form in the response. It needs to be decoded afterward to further work with it as an image.
Example of decoding and showing the image with the PIL library:
Example of decoding and showing the image with OpenCV library:
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image โ processed image - output image that passed through the flow, but without any heatmaps or rectangles (e.g. if the image is scaled during the flow, it returns a scaled image).
annotated_image โ processed image with annotations - heatmaps over the image.
heatmap - response contains only the heatmaps over the image (without the image).
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For all those image response types, the serialized context is by default added to the headers with the header title 'ContextBase64utf'. To get it to JSON form, you can use this code:
Context in body
When getting an image in the response, by default the context is sent in headers. However, with a very large number of defects, the maximum header length limit can be reached. To solve this, you can use the option to send context in the body of the response together with the image and get the image length in a header 'ImageLen' to be able to divide the two parts after. To activate this mode, add the following to the request:
Example of the usage in Python code when getting the last image:
Testing the API functionality
If you have a running project on a port e.g. 8000, you can test the API by accessing this address in your browser (if PEKAT is running on the local computer, otherwise replace localhost with the IP address of the remote PC):
This displays the testing app, where you can choose to display the last processed image or send a new image to analyze. You can choose the Response type - Context, Image, Annotated image (image with a heatmap), or Heatmap. If the project has Secure image analyze enabled, you also need to enter the API key.
If Analyze image is chosen, you can also select the image that will be sent through the API. If the response type is different than the Context, the default behavior is that the image is sent in the body of the response and the context is sent in the headers - to change this and send both in the body, check the box with Context in the body. The detail of the request structure will be displayed.
After you click Send, you will also see the structure of the response in the blue info box, context (as you would see it in Inspection), and optionally an image based on the response type.
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