Yolo-v7-Quantized
Quantized real‑time object detection optimized for mobile and edge.
YoloV7 is a machine learning model that predicts bounding boxes and classes of objects in an image. This model is post‑training quantized to int8 using samples from the COCO dataset.
Technical Details
Model checkpoint:YoloV7 Tiny
Input resolution:720p (720x1280)
Number of parameters:6.24M
Model size:6.23 MB
Applicable Scenarios
- Factory Automation
- Robotic Navigation
- Camera
Tags
- real-time
- quantized
Supported IoT Devices
- QCS6490 (Proxy)
- QCS8250 (Proxy)
- QCS8550 (Proxy)
- RB3 Gen 2 (Proxy)
- RB5 (Proxy)
Supported IoT Chipsets
- Qualcomm® QCS6490 (Proxy)
- Qualcomm® QCS8250 (Proxy)
- Qualcomm® QCS8550 (Proxy)
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