This is a demo of the Dash interactive Python framework developed by Plotly.
Dash abstracts away all of the technologies and protocols required to build an interactive web-based application and is a simple and effective way to bind a user interface around your Python code.
To learn more check out our documentation.
The videos are displayed using a community-maintained Dash video component. It is made by two Plotly community contributors. You can find the source code here.
All videos used are open-sourced under Creative Commons. The [original links can be found here](data/Original Footage.md).
The object detection model is the MobileNet v1, made by Google and trained on the COCO dataset. You can find their implementation on their official Github repo. You are encouraged to try this app with other models.
The data displayed in the app are pregenerated for demo purposes. To generate the csv files containing the objects detected for each frame, as well as the output video with bounding boxes, please refer to utils/generate_video_data.py. You will need the latest version of tensorflow and OpenCV, as well as the frozen graph ssd_mobilenet_v1_coco, that you can download in the Model Zoo. Make sure to place the frozen graph inside the same folder as generate_video_data.py, i.e. utils.
The following are screenshots for the app in this repo:
