Yolo-v7
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.
Technical Details
Model checkpoint:YoloV7 Tiny
Input resolution:720p (720x1280)
Number of parameters:6.39M
Model size:24.4 MB
Applicable Scenarios
- Factory Automation
- Robotic Navigation
- Camera
Supported Form Factors
- Phone
- Tablet
- IoT
- XR
Tags
- real-timeA “real-time” model can typically achieve 5-60 predictions per second. This translates to latency ranging up to 200 ms per prediction.
Supported Devices
- Google Pixel 3
- Google Pixel 3a
- Google Pixel 3a XL
- Google Pixel 4
- Google Pixel 4a
- Google Pixel 5a 5G
- QCS8550 (Proxy)
- SA8255 (Proxy)
- SA8650 (Proxy)
- SA8775 (Proxy)
- 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
- Xiaomi 12
- Xiaomi 12 Pro
Supported Chipsets
- Qualcomm® QCS8550
- Qualcomm® SA8255P
- Qualcomm® SA8650P
- Qualcomm® SA8775P
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
- Snapdragon® X Elite