This model counts detected objects in an image and returns a list of detected objects and their count.
It is based on YOLOv4. YOLOv4 uses an extended Convolutional Neural Network architecture. For more information about the underlying Neural Network and further resources, you can read our blog post: https://ubiops.com/how-to-deploy-yolov4-on-ubiops/. It is implemented on UbiOps with ONNX for speedup.
Detects objects in an image and returns a list of detected objects and their count. Expects a jpg./jpeg. or .png file as input. Upload your image and click ‘‘run code”.
This model is intended for demonstration and testing purposes only. UbiOps is not liable for any damages arising from the use or inability to use any of the models and applications listed on the UbiOps Community Model pages. Even though UbiOps and our partners carefully created and optimized these models, it is always advised to benchmark and check the respective functionality before applying it in any production setting.
Last modified: 30-11-2021
This model counts detected objects in an image and returns a list of detected objects and their number.