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.

10.8ms
Inference Time
0-57MB
Memory Usage
203NPU
12CPU
Layers

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

Licenses

Source Model:GPL-3.0
Deployable Model:GPL-3.0

Tags

  • real-time
    A “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)
  • 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
  • Snapdragon® 8 Gen 1 Mobile
  • Snapdragon® 8 Gen 2 Mobile
  • Snapdragon® 8 Gen 3 Mobile
  • Snapdragon® 888 Mobile
  • Snapdragon® X Elite