Yolo-NAS-Quantized
Quantized real‑time object detection optimized for mobile and edge.
YoloNAS 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:YoloNAS Small
Input resolution:640x640
Number of parameters:12.2M
Model size:12.1 MB
Applicable Scenarios
- Factory Automation
- Robotic Navigation
- Camera
Supported Form Factors
- Phone
- Tablet
- IoT
- XR
Tags
- real-time
- quantized
Supported Devices
- QCS6490 (Proxy)
- QCS8550 (Proxy)
- RB3 Gen 2 (Proxy)
- SA7255P ADP
- SA8255 (Proxy)
- SA8295P ADP
- SA8650 (Proxy)
- SA8775P ADP
- Samsung Galaxy S21
- Samsung Galaxy S21 Ultra
- Samsung Galaxy S21+
- Samsung Galaxy S22 5G
- Samsung Galaxy S22 Ultra 5G
- Samsung Galaxy S22+ 5G
- Samsung Galaxy S23
- Samsung Galaxy S23 Ultra
- Samsung Galaxy S23+
- Samsung Galaxy S24
- Samsung Galaxy S24 Ultra
- Samsung Galaxy S24+
- Samsung Galaxy Tab S8
- Snapdragon 8 Elite QRD
- Snapdragon X Elite CRD
- Snapdragon X Plus 8-Core CRD
- Xiaomi 12
- Xiaomi 12 Pro
Supported Chipsets
- Qualcomm® QCS6490 (Proxy)
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® SA7255P
- Qualcomm® SA8255P (Proxy)
- Qualcomm® SA8295P
- Qualcomm® SA8650P (Proxy)
- Qualcomm® SA8775P
- Snapdragon® 8 Elite Mobile
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
- Snapdragon® X Elite
- Snapdragon® X Plus 8-Core
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