Phoenix - Your AI AssistantWindow Dimensions API OpenCV Python
- Posted:
- Proposals: 27
- Remote
- #4255375
- OPPORTUNITY
- Expired
Helsinki 
Description
Experience Level: Expert
An API is to be provided that receives an image file of a window section taken for a construction project. The image comes from the camera of a mobile device (smartphone/tablet) and meets the following requirements:
The window is photographed straight from the front.
The window is rectangular or square.
The image is well-lit.
A reference object (e.g., a green cube) with known dimensions can be placed in the image.
The API detects the object (window or window hole) and generates the outer dimensions. The tolerance should be as low as possible (max 1.0 - 1.5 cm).
The API returns a JSON with the following properties:
width: Width of the window hole
height: Height of the window hole
imagepath: Image path to the picture with the frame and dimensions, so that it can be checked if the section was captured correctly
Only the API needs to be programmed. The image illustrates Step 2 and Step 3.
Ideally, the project will be implemented in Python.
The window is photographed straight from the front.
The window is rectangular or square.
The image is well-lit.
A reference object (e.g., a green cube) with known dimensions can be placed in the image.
The API detects the object (window or window hole) and generates the outer dimensions. The tolerance should be as low as possible (max 1.0 - 1.5 cm).
The API returns a JSON with the following properties:
width: Width of the window hole
height: Height of the window hole
imagepath: Image path to the picture with the frame and dimensions, so that it can be checked if the section was captured correctly
Only the API needs to be programmed. The image illustrates Step 2 and Step 3.
Ideally, the project will be implemented in Python.
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Is the API required to handle situations where the reference object is placed at an angle or not entirely in the frame?
Is there a preferred method or framework for developing the API (e.g., Flask, FastAPI)?
How should the API handle images that do not meet the requirements (e.g., no reference object, poor lighting, non-rectangular windows)?
Are there any specific datasets that the API needs to be tested against?