✔ REAL TIME HUMAN DETECTION & COUNTING

• A tensorflow based Faster RCNN inception v2 python model to detect and count humans in real time images, videos & camera.
• Used pre-trained frozen_inference_graph.pb frozen graph to handle the detection.
• Visualize the data using Enumeration Plot and Avg. Accuracy Plot.

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📌REQUIREMENTS :

• python 3
• tkinter
• messagebox
• PIL
• cv2
• argparse
• matplotlib.pyplot
• numpy
• time
• os
• tensorflow
• fpdf

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📌How this Script works :

• User just need to download the file and run the main.py on their local system.
• On the starting window of the application, user will be able to see START and EXIT option, using which user can start the application or exit from the application.
• When user starts the application using START button, a new window will open, which allows user with options like, DETECT FROM IMAGE, DETECT FROM VIDEO or DETECT FROM CAMERA.
• When user selects any of the first two option, he/she needs to select the respective files using SELECT button.
• User can preview the selected file using PREVIEW button, and detect and count the humans using DETECT button.
• And when user selects, the last option of detecting through camera, user need to open the Camera, using OPEN CAMERA button, As soon as camera opens, detection process will start.
• After detection process gets completed or user manually completes it, two graph get plotted,
  • 1.) Enumeration Plot(Human Count Vs. time) and
  • 2.) Avg. Accuracy Plot(Avg. Accuracy Vs. time).
• Along with this two plots, an option to generate crowd report also appears, On clicking on it, a crowd report in form of PDF is generated ans saved autmatically at the project file location.
• In the crowd report genrated, there will be information like, What is Max Human Count, Max Accuracy, Max Avg. Accuracy, and also a two line status about crowd.

📌Purrpose :

• This scripts helps user to easily get the count of human through real time image, video or camera, and thereafter also analysis of crowd through crowd report.

📌Compilation Steps :

• Install all the required libraries.
• After that download the code file, and run main.py on local system.
• Then the script will start running and user can explore it by detecting the human and also getting the count of it.

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📌SCREENSHOTS :

• Image:

• Video:

• Camera:

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🌟Stargazers Over Time:

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🌟Forkers Over Time:

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📌Contributors: