build an API for automated car image background removal and placement within a virtual showroom environment.
Budget: $250 – $750 USD
We are developing a web-based tool that allows users to upload car images and have them automatically placed in a pre-defined 3D showroom environment. This API will require the following functionalities:
Image Classification:
Distinguish between car images showing the exterior or interior.
Images identified as interior will be excluded from further processing.
Background Removal (Exterior Images Only):
Remove the background from car images classified as "exterior."
3D Bounding Box Generation:
Analyze the remaining image to detect the car's orientation and create a corresponding 3D bounding box.
Virtual Showroom Integration:
Utilize WebGL or Blender to generate a rendered image of the virtual showroom environment, matching the car's orientation from step 3.
Image Composition:
Overlay the processed car image (with transparent background) onto the generated showroom image.
Shadow Enhancement (Optional):
Implement an algorithm to add a realistic-looking shadow to the car within the virtual showroom scene.
Technical Skills & Experience:
Strong proficiency in back-end development languages (Python, Java, etc.)
Experience with image processing libraries (OpenCV, scikit-image)
Familiarity with 3D graphics frameworks (WebGL, Blender) or related APIs
Knowledge of machine learning concepts for potential use in image classification and background removal
Additional Information:
Please specify the following in your application:
Preferred tech stack for this project
Whether you plan to incorporate machine learning models for any of the mentioned steps
We look forward to working with a skilled developer to bring this exciting project to life!
An example: https://www.car-cutter.com/showroom-lists-de/15
Image Classification:
Distinguish between car images showing the exterior or interior.
Images identified as interior will be excluded from further processing.
Background Removal (Exterior Images Only):
Remove the background from car images classified as "exterior."
3D Bounding Box Generation:
Analyze the remaining image to detect the car's orientation and create a corresponding 3D bounding box.
Virtual Showroom Integration:
Utilize WebGL or Blender to generate a rendered image of the virtual showroom environment, matching the car's orientation from step 3.
Image Composition:
Overlay the processed car image (with transparent background) onto the generated showroom image.
Shadow Enhancement (Optional):
Implement an algorithm to add a realistic-looking shadow to the car within the virtual showroom scene.
Technical Skills & Experience:
Strong proficiency in back-end development languages (Python, Java, etc.)
Experience with image processing libraries (OpenCV, scikit-image)
Familiarity with 3D graphics frameworks (WebGL, Blender) or related APIs
Knowledge of machine learning concepts for potential use in image classification and background removal
Additional Information:
Please specify the following in your application:
Preferred tech stack for this project
Whether you plan to incorporate machine learning models for any of the mentioned steps
We look forward to working with a skilled developer to bring this exciting project to life!
An example: https://www.car-cutter.com/showroom-lists-de/15