Computer Vision Application for Warehouse Inventory Classification and Counting
Budget: ₹12,500 – ₹37,500 INR
Project Overview:
We're seeking an experienced freelancer to develop a computer vision application using Python to classify and count inventory from a warehouse conveyor using a camera. The application will be used to count purchase inventory in retail, distributor, and wholesale warehouses.
Inputs -
Product Images from different angles for training
Image/Video stream from of products from a camera.
Outputs-
Products List from the video/image along with Count
Other informations – Product price, Batch, Expiry (If readable)
Project requirements -
Accuracy: Achieve high accuracy (>95%) in inventory classification and counting.
Efficiency: Optimize the application for real-time processing and efficient use of computational resources.
Scalability: Design the application to handle varying volumes of images and videos.
Technical Requirements:
1. Computer Vision Expertise, Preferrably YOLO: Proven experience in computer vision, image processing, and object detection. YOLO experience or knowledge would be highly advantag. Here is a sample YOLO demo
https://www.youtube.com/watch?v=r0RspiLG260&t=9s
2. Python Proficiency: Strong proficiency in Python programming language, including popular libraries such as OpenCV, TensorFlow, and PyTorch.
3. Image/Video Processing: Experience with image and video processing techniques, including object detection, segmentation, and classification.
4. Machine Learning: Familiarity with machine learning concepts and algorithms, including supervised and unsupervised learning.
5. Deep Learning: Experience with deep learning frameworks, such as TensorFlow or PyTorch, and architectures, such as CNNs and RNNs.
Deliverables:
1. Source Code: Well-documented and commented source code for the computer vision application.
2. Documentation: Technical documentation, including architecture, design, and implementation details.
3. Testing: Thorough testing and validation of the application to ensure accuracy and efficiency.
Nice-to-Have Skills:
1. Experience with Warehouse Management Systems: Familiarity with warehouse management systems and inventory management software.
2. Knowledge of Retail, Distributor, or Wholesale Industry: Understanding of the retail, distributor, or wholesale industry and its inventory management challenges.
What We Offer:
1. Competitive Compensation: We offer competitive compensation for the successful completion of the project.
2. Opportunity for Future Collaboration: We're looking for a long-term partner to collaborate on future computer vision projects.
We would seek an initial POC product developed with YOLO which can count a limited set of products.
If you're an experienced computer vision developer with a strong background in Python, machine learning, and deep learning, we'd love to hear from you!
We're seeking an experienced freelancer to develop a computer vision application using Python to classify and count inventory from a warehouse conveyor using a camera. The application will be used to count purchase inventory in retail, distributor, and wholesale warehouses.
Inputs -
Product Images from different angles for training
Image/Video stream from of products from a camera.
Outputs-
Products List from the video/image along with Count
Other informations – Product price, Batch, Expiry (If readable)
Project requirements -
Accuracy: Achieve high accuracy (>95%) in inventory classification and counting.
Efficiency: Optimize the application for real-time processing and efficient use of computational resources.
Scalability: Design the application to handle varying volumes of images and videos.
Technical Requirements:
1. Computer Vision Expertise, Preferrably YOLO: Proven experience in computer vision, image processing, and object detection. YOLO experience or knowledge would be highly advantag. Here is a sample YOLO demo
https://www.youtube.com/watch?v=r0RspiLG260&t=9s
2. Python Proficiency: Strong proficiency in Python programming language, including popular libraries such as OpenCV, TensorFlow, and PyTorch.
3. Image/Video Processing: Experience with image and video processing techniques, including object detection, segmentation, and classification.
4. Machine Learning: Familiarity with machine learning concepts and algorithms, including supervised and unsupervised learning.
5. Deep Learning: Experience with deep learning frameworks, such as TensorFlow or PyTorch, and architectures, such as CNNs and RNNs.
Deliverables:
1. Source Code: Well-documented and commented source code for the computer vision application.
2. Documentation: Technical documentation, including architecture, design, and implementation details.
3. Testing: Thorough testing and validation of the application to ensure accuracy and efficiency.
Nice-to-Have Skills:
1. Experience with Warehouse Management Systems: Familiarity with warehouse management systems and inventory management software.
2. Knowledge of Retail, Distributor, or Wholesale Industry: Understanding of the retail, distributor, or wholesale industry and its inventory management challenges.
What We Offer:
1. Competitive Compensation: We offer competitive compensation for the successful completion of the project.
2. Opportunity for Future Collaboration: We're looking for a long-term partner to collaborate on future computer vision projects.
We would seek an initial POC product developed with YOLO which can count a limited set of products.
If you're an experienced computer vision developer with a strong background in Python, machine learning, and deep learning, we'd love to hear from you!