AI for Jute Sack Counting via CCTV
Budget: ₹12,500 – ₹37,500 INR
Job Title:
AI Developer Needed to Build Jute Sack Counting System Using Existing CCTV Footage
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Job Description:
We are looking for an experienced AI/Computer Vision freelancer to develop a custom solution that automatically tracks and counts jute sacks being loaded and unloaded between trucks and our warehouse using our existing CCTV camera setup.
This is a one-time project aimed at increasing transparency, reducing pilferage, and improving efficiency in warehouse operations.
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Responsibilities:
•Analyze sample CCTV footage and assess visibility for sack detection.
•Annotate video frames/images for jute sack detection (or guide us on annotation).
•Train an object detection model (preferably using YOLOv8 or a similar framework).
•Develop a lightweight script or application to:
•Detect and count sacks in live or recorded video feeds.
•Log counts with timestamps (e.g., CSV, Excel, or simple dashboard).
•(Optional) Alert for discrepancies between expected and actual count.
•Set up the system to run on a local device (NVIDIA Jetson Nano, PC, or Raspberry Pi if needed).
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Requirements:
•Proven experience with computer vision, YOLO models (v5/v8), and OpenCV
•Experience working with CCTV/IP camera video feeds (RTSP or DVR/NVR)
•Familiarity with Python and lightweight local deployment
•Ability to work independently and deliver a practical, reliable solution
•Bonus: Experience with edge devices like Jetson Nano or Coral TPU
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Deliverables:
1.Trained object detection model optimized for detecting jute sacks.
2.Python-based script or application that:
•Connects to live or saved CCTV footage
•Detects and counts sacks in real time or batch mode
•Outputs logs/reports of loading/unloading activity
3.Documentation and basic usage guide
4.Support during initial testing and deployment
⸻
Project Budget: ₹5,000 – ₹12,000 (negotiable based on experience and deliverables)
Timeline: 2–3 weeks preferred
Location: CF38+CV, Additional Latur MIDC, Harangul Bk.,Latur, Maharashtra 413531 (must be available for occasional calls and testing coordination)
⸻
To Apply:
Please share:
• Your past experience with similar computer vision projects
• A brief outline of how you’d approach this project
• Links to any relevant GitHub or project demos
AI Developer Needed to Build Jute Sack Counting System Using Existing CCTV Footage
⸻
Job Description:
We are looking for an experienced AI/Computer Vision freelancer to develop a custom solution that automatically tracks and counts jute sacks being loaded and unloaded between trucks and our warehouse using our existing CCTV camera setup.
This is a one-time project aimed at increasing transparency, reducing pilferage, and improving efficiency in warehouse operations.
⸻
Responsibilities:
•Analyze sample CCTV footage and assess visibility for sack detection.
•Annotate video frames/images for jute sack detection (or guide us on annotation).
•Train an object detection model (preferably using YOLOv8 or a similar framework).
•Develop a lightweight script or application to:
•Detect and count sacks in live or recorded video feeds.
•Log counts with timestamps (e.g., CSV, Excel, or simple dashboard).
•(Optional) Alert for discrepancies between expected and actual count.
•Set up the system to run on a local device (NVIDIA Jetson Nano, PC, or Raspberry Pi if needed).
⸻
Requirements:
•Proven experience with computer vision, YOLO models (v5/v8), and OpenCV
•Experience working with CCTV/IP camera video feeds (RTSP or DVR/NVR)
•Familiarity with Python and lightweight local deployment
•Ability to work independently and deliver a practical, reliable solution
•Bonus: Experience with edge devices like Jetson Nano or Coral TPU
⸻
Deliverables:
1.Trained object detection model optimized for detecting jute sacks.
2.Python-based script or application that:
•Connects to live or saved CCTV footage
•Detects and counts sacks in real time or batch mode
•Outputs logs/reports of loading/unloading activity
3.Documentation and basic usage guide
4.Support during initial testing and deployment
⸻
Project Budget: ₹5,000 – ₹12,000 (negotiable based on experience and deliverables)
Timeline: 2–3 weeks preferred
Location: CF38+CV, Additional Latur MIDC, Harangul Bk.,Latur, Maharashtra 413531 (must be available for occasional calls and testing coordination)
⸻
To Apply:
Please share:
• Your past experience with similar computer vision projects
• A brief outline of how you’d approach this project
• Links to any relevant GitHub or project demos
Related categories:
Python
Video Services
Software Architecture
C++ Programming
Computer Vision
Object Detection
YOLO
AI Development