Computer Vision Model for Waste Detection and Analytics
Budget: $30 – $250 USD
Build a Computer Vision Model for Waste Detection (YOLO / VertexAI / Roboflow)
Project Description
We’re developing a waste intelligence and analytics dashboard and need a computer vision expert to train an object detection model on our collected images.
We currently have 100–300 labeled waste images (plastics, paper, e-waste, metal, etc.) and are looking for someone who can quickly train and optimize a detection model that can:
Identify and classify different types of waste accurately
Provide confidence scores for each detection
Deliver results that can integrate later into a dashboard or reporting layer
The ideal freelancer should have hands-on experience with YOLOv8, Roboflow, OpenAI Vision APIs, or Google VertexAI (any of these is fine — whichever gives the most accurate results).
Deliverables
Trained and tested object detection model
Model file(s) + inference code or deployment-ready endpoint
Confidence score outputs for each class
Ability to export data into Excel/data warehouse platform using API's
Brief documentation or walkthrough on how to reuse/retrain the model later
Budget & Timeline
Budget: $50 (fixed)
Timeline: 7 days from the date we provide the dataset
We’re not looking for anything over-engineered — just a clean, functional MVP-level model that helps us analyze waste categories visually.
Bonus Points
Prior experience working with waste recognition or sustainability projects
Ability to explain model performance metrics simply (precision, recall, F1)
Familiarity with exporting to platforms like Roboflow or VertexAI for scalable deployment
Our Goal
We believe in clear communication and quick collaboration — this is meant to be a win-win pilot project.
How to Apply
Please share:
A few lines about your past work in computer vision / object detection.
The tech stack or platform you’d prefer (YOLO, Roboflow, VertexAI, etc.).
Estimated accuracy or validation plan you’d follow for the dataset.
Project Description
We’re developing a waste intelligence and analytics dashboard and need a computer vision expert to train an object detection model on our collected images.
We currently have 100–300 labeled waste images (plastics, paper, e-waste, metal, etc.) and are looking for someone who can quickly train and optimize a detection model that can:
Identify and classify different types of waste accurately
Provide confidence scores for each detection
Deliver results that can integrate later into a dashboard or reporting layer
The ideal freelancer should have hands-on experience with YOLOv8, Roboflow, OpenAI Vision APIs, or Google VertexAI (any of these is fine — whichever gives the most accurate results).
Deliverables
Trained and tested object detection model
Model file(s) + inference code or deployment-ready endpoint
Confidence score outputs for each class
Ability to export data into Excel/data warehouse platform using API's
Brief documentation or walkthrough on how to reuse/retrain the model later
Budget & Timeline
Budget: $50 (fixed)
Timeline: 7 days from the date we provide the dataset
We’re not looking for anything over-engineered — just a clean, functional MVP-level model that helps us analyze waste categories visually.
Bonus Points
Prior experience working with waste recognition or sustainability projects
Ability to explain model performance metrics simply (precision, recall, F1)
Familiarity with exporting to platforms like Roboflow or VertexAI for scalable deployment
Our Goal
We believe in clear communication and quick collaboration — this is meant to be a win-win pilot project.
How to Apply
Please share:
A few lines about your past work in computer vision / object detection.
The tech stack or platform you’d prefer (YOLO, Roboflow, VertexAI, etc.).
Estimated accuracy or validation plan you’d follow for the dataset.