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Joint Object Detection and Depth Estimation in Image

Repository for the Deep Learning course project:

  • Milad Samimifar
  • Pooria Ashrafian

Object detection method that can simultaneously estimate the positions and depth of the objects from images. (Based on NYU-Depth V2 dataset)

The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect.


Joint object detection and depth estimation web app using streamlit (recomended): Object_detection_web_app_streamlit repository

  1. Download yolov3 weights and put it in Object_detection_web_app_streamlit folder:
wget -nc https://pjreddie.com/media/files/yolov3.weights -P Object_detection_web_app_streamlit
  1. Download our Unet depth model weights and put it in ./models_depth/Unet folder:

Shell commmand:

gdown --id 1fvzPVqKj46WjaYw6OUr1a38KblWkGC4W -O ./models_depth/Unet/2.h5 # weights

gdown --id 1g685-v1qGv6NBE7nhY0LSQDgUemJXarc -O ./models_depth/Unet/2.json # model(json file)
  1. install requirements:
pip install streamlit opencv-python black
  1. Execute:
cd Object_detection_web_app_streamlit
streamlit run ./src/app.py

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Joint object detection and depth estimation web app using django: Object_detection_web_app repository

  1. Download yolov3 weights and put it in Object_detection_web_app folder:
wget -nc https://pjreddie.com/media/files/yolov3.weights -P Object_detection_web_app
  1. Install requirements:
pip install -r ./Object_detection_web_app/requirements.txt
  1. Execute the code below: (Only once)
cd Object_detection_web_app
python manage.py collectstatic
  1. Execute:
python manage.py runserver

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Joint object detection and depth estimation: demo

Joint_notebook.ipynb:

  • Download dataset and preprocessing
  • Train Unet model for depth estimation [1]

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  • Yolov3 Object detection

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  • Joint model and test

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Reference

[1] Ibraheem Alhashim and Peter Wonka. High quality monocular depth estimation via transfer learning. arXiv preprint arXiv:1812.11941, 2018.