Contact person: Business Client

Phone:Show

Email:Show

Location: Chicago, United States

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"AI Vehicle Visualizer (Tint + Ceramic Preview) — No Custom AI Training

Description:
I need a simple AI vehicle visualizer for my auto detailing app (built in FlutterFlow). This project does not require custom ML model training, datasets, or deep learning development. Please do NOT bid if your solution requires labeled training data or creating a new AI model.

I need a lightweight, API-based solution:

Core features:
• User uploads a photo of their vehicle
• System uses an EXISTING segmentation or masking model (no training)
• User selects one or more options:
• Window tint % (5%, 15%, 20%, etc.)
• Ceramic coating gloss level
• AI applies visual modifications:
• Tint overlay on windows
• Gloss/shine enhancement on paint
• Return a preview image that shows tint + ceramic combined
• Final output must look realistic enough for customer previews
• Results delivered via API so my developer can integrate inside FlutterFlow

Requirements:
• Must use pre-trained models (e.g., segmentation APIs, StableDiffusion ControlNet, Replicate, etc.)
• No dataset collection
• No custom neural network training
• No multi-thousand-dollar ML pipelines
• Must be efficient and mobile-friendly
• I only need the visualizer engine/API + documentation to connect to FF

Budget: $1,500 – $3,000
Timeline: 4 – 6 weeks
Tech stack options (your choice):
• ControlNet + StableDiffusion
• Replicate API
• TensorFlowJS segmentation models
• Any reliable pre-trained solution

Please send:
• Examples of similar image editing or segmentation work
• Confirmation that your approach does NOT require custom training" (client-provided description)