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Generate heatmap from the video for usage analysis.

Project description


To generate the heatmaps from the specific camera’s in a location.

To Use Simply do::
>>> generate_heatmap -i /Users/abc/heat_data/ew_grnd -p /Users/abc/heat_data/ewPickle -r EWGrndMorning -hl /Users/abc/heat_data/heatmaps/
        -v /Users/abc/heat_data/CCTV_Videos/ -b /Users/abc/heat_data/baseImages/ewGcL.png -pass “XXXXXX” -u -hc 1234


CV2, you can install opencv for your specific platforms either by using conda , miniconda or manually downloading and installing it.

External installation links, using conda and windows.


generate_heatmap is a command line program to generate heatmaps of the video you have in your local system. Its a great way to understand how your space is being used by the community or Members. It requires Python Interpreter, version 3.5+, and its not platform specific. It should work on Ubuntu, Windows or on MacOs.


  1. (-v or –vloc): Give the videos folder location, Download the videos and keep it in this folder.
  2. (-i or –imgloc): Create a images folder, where all images generated from the videos will be stored.
  3. (-p or –pickleloc): Create a pickle folder, pickle file will be stored to generate heatmap from it.
  4. (-r or –reqdata): Give name to your heatmap image, name of the output heatmap image.
  5. (-hl or –heatloc): Heatmap Folder, where final heatmap image will be stored.
  6. (-b or –baseurl): Keep the base image of the video in one place and pass it as, (This image will be a reference image for the downloaded videos.)

Optional Parameters:

  1. -pass, password of the api for your authentication.
  2. -u , API EndPoint where heatmap image will be sent.
  3. -hc, heatcode to identify which req image is this.


1.Goes through the videos folder, and generates the images from all the videos available in the folder, It can process multiple videos also in a folder for same camera view in a folder.

2.Processing of the images is the next step, It processess all the images in a folder generated by cv2, compares all the images and generates the pickle file of the heatmap.

3.Heatmap generation is the last step, by taking the pickle file generate the heatmap image.

Project details

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Filename, size & hash SHA256 hash help File type Python version Upload date
generate_heatmap-0.2.1-py3-none-any.whl (9.9 kB) Copy SHA256 hash SHA256 Wheel py3 Mar 29, 2018

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