Yolo-v4
Real‑time object detection optimized for mobile and edge.
YoloV4 is a machine learning model that predicts bounding boxes and classes of objects in an image.
Note: Yolo-v4 cannot be downloaded directly due to licensing restrictions. You can export a model ready for on-device deployment using the AI Hub service.
Not supported
This model is currently not supported on any IoT chipset.
To see performance metrics for this model on other chipsets, click the button below.
View for other chipsetsTechnical Details
Input resolution:416x416
Model checkpoint:YoloV4 Tiny
Model size (float):23.1 MB
Model size (w8a16):6.07 MB
Number of parameters:6.06M
Applicable Scenarios
- Factory Automation
- Robotic Navigation
- Camera
License
Model:MIT
Tags
- real-time
Supported IoT Devices
- Arduino VENTUNO Q
- Dragonwing IQ-9075 EVK
- Dragonwing IQ-X5121
- Dragonwing IQ-X7181
- Dragonwing Q-6690 MTP
- Dragonwing Q-7790
- Dragonwing Q-8750
- Dragonwing RB3 Gen 2 Vision Kit
- QCS8550 (Proxy)
Supported IoT Chipsets
- Qualcomm® Dragonwing™ Q-6690
- Qualcomm® QCS5121
- Qualcomm® Dragonwing™ QCS6490
- Qualcomm® Dragonwing™ IQ-X7181
- Qualcomm® Dragonwing™ Q-7790
- Qualcomm® Dragonwing™ IQ-8275
- Qualcomm® Dragonwing™ QCS8550 (Proxy)
- Qualcomm® Dragonwing™ Q-8750
- Qualcomm® Dragonwing™ IQ-9075
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