Merge pull request DhanushNehru#322 from Stonebanks-js/master

Add Image Overlay & Facial Landmark Detection to face_reaction.py

Author: DhanushNehru

Face Reaction/README.md

@@ -0,0 +1,79 @@
+
+# Face Reaction with Custom Emojis and Emotion History
+
+This project uses OpenCV and FER (Facial Expression Recognition) to capture live video from the webcam, detect facial expressions in real time, and display corresponding emoji images for each detected emotion. Additionally, this enhanced version features custom emoji support and emotion detection history tracking, which provides a list of recently detected emotions.
+
+
+
+
+## Acknowledgements
+
+ We would like to express our sincere gratitude to the following:
+
+OpenCV for providing powerful tools for computer vision, enabling us to process real-time video feeds with ease.
+
+FER (Facial Expression Recognition) for simplifying the process of emotion detection with advanced facial expression recognition algorithms.
+
+The open-source community for providing constant support, knowledge, and resources that have helped improve and evolve this project.
+
+Contributors to this repository for their efforts in enhancing the functionality and maintaining the quality of the code.
+
+Special thanks to all the libraries, frameworks, and developers whose work has made this project possible!
+
+
+## Features Added to Project 
+
+Real-Time Emotion Detection:
+
+The system detects emotions such as angry, happy, sad, surprise, and more in real time using the FER library.
+Custom Emojis:
+
+Users can provide their own custom emoji images to represent emotions.
+Emotion Detection History:
+
+The program keeps track of the last 10 detected emotions and displays them on the screen, allowing users to see the emotion flow during the session.
+Smooth Emoji Overlay:
+
+The corresponding emoji for the detected emotion is displayed on the video feed in a designated corner of the screen.
+## Prerequisites
+
+Ensure that you have the following installed before running the script:
+
+Python 3.x
+OpenCV
+Numpy
+FER (Facial Expression Recognition)
+
+You can install the required libraries by running:
+pip install opencv-python numpy fer
+
+
+## How to Run
+
+Clone the Repository :
+
+git clone https://github.com/your-repo/face-reaction.git
+
+Run the Python script:
+
+python face_reaction.py
+
+
+## Custom Emoji Support
+
+To add your custom emoji, replace the URLs or paths in the script with the path to your custom emoji image files. The supported emotions include angry, happy, sad, disgust, fear, surprise, and neutral.
+
+
+## Code Explanation
+
+Emotion Detection: The FER library is used to detect the dominant emotion in the video frame, with the highest probability score.
+
+Custom Emoji Overlay: Based on the detected emotion, the corresponding emoji image is resized and overlaid on the video feed.
+
+Emotion History: The recent emotions are displayed at the top-left corner of the video frame, showing the last 10 detected emotions during the session.
+
+
+## Future Improvements 
+
+Support for additional facial expressions.
+Integration with cloud services for storing emotion history.

Face Reaction/app.py

@@ -1,43 +1,72 @@
 import cv2
 import numpy as np
 from fer import FER
+import os
+import json
 
-scr = cv2.VideoCapture(0) #30fps
+# Load custom emojis from a config file (custom_emojis.json)
+def load_custom_emojis(config_file='custom_emojis.json'):
+    if os.path.exists(config_file):
+        with open(config_file, 'r') as file:
+            return json.load(file)
+    return {}
+
+# Save the emotion detection history
+def save_emotion_history(history, filename='emotion_history.txt'):
+    with open(filename, 'a') as file:
+        for emotion in history:
+            file.write(f"{emotion}\n")
+
+# Initialize the webcam
+scr = cv2.VideoCapture(0)  # 30fps
 scr.set(3, 640)
 scr.set(4, 480)
 
-#init FRE (Facial expression recognition from images)
+# Initialize FER (Facial Expression Recognition)
 detector = FER(mtcnn=True)
 
-while True:
+# Load custom emojis
+custom_emojis = load_custom_emojis()
 
-    ret,frame = scr.read()
-    # frame = cv2.flip(frame,1)
+# Initialize emotion detection history
+emotion_history = []
 
-    #return emotion name and % of true detection
+while True:
+    ret, frame = scr.read()
+
+    # Return emotion name and % of true detection
     emotion, score = detector.top_emotion(frame)
 
-    print(emotion,score)
-    if emotion == 'angry':
-        emoj = cv2.imread('https://i.ibb.co/QN0gqNH/angry.png')
-    elif emotion == 'disgust':
-        emoj = cv2.imread('https://i.ibb.co/tJDxrhD/disgust.png')
-    elif emotion == 'fear':
-        emoj = cv2.imread('https://i.ibb.co/yBczSFB/fear.png')
-    elif emotion == 'happy':
-        emoj = cv2.imread('https://i.ibb.co/g6DW0Cf/happy.png')
-    elif emotion == 'sad':
-        emoj = cv2.imread('https://i.ibb.co/NyF0sDq/sad.png')
-    elif emotion == 'surprise':
-        emoj = cv2.imread('https://i.ibb.co/D4rDyfM/surprise.png')
-    elif emotion == 'neutral':
-        emoj = cv2.imread('https://i.ibb.co/KX7VSjh/neutral.png')
-    else:
-        emoj = cv2.imread('https://i.ibb.co/LdnS9nL/none.png')
+    # Append detected emotion to the history
+    emotion_history.append(emotion)
+    # Optionally save the history to a file (uncomment to enable)
+    # save_emotion_history(emotion_history)
 
+    print(emotion, score)
 
-    #Adding Image on Screen
-    
+    # Use custom emoji if available, otherwise fall back to default
+    if emotion in custom_emojis:
+        emoj = cv2.imread(custom_emojis[emotion])
+    else:
+        # Default emojis if no custom emojis are set
+        if emotion == 'angry':
+            emoj = cv2.imread('https://i.ibb.co/QN0gqNH/angry.png')
+        elif emotion == 'disgust':
+            emoj = cv2.imread('https://i.ibb.co/tJDxrhD/disgust.png')
+        elif emotion == 'fear':
+            emoj = cv2.imread('https://i.ibb.co/yBczSFB/fear.png')
+        elif emotion == 'happy':
+            emoj = cv2.imread('https://i.ibb.co/g6DW0Cf/happy.png')
+        elif emotion == 'sad':
+            emoj = cv2.imread('https://i.ibb.co/NyF0sDq/sad.png')
+        elif emotion == 'surprise':
+            emoj = cv2.imread('https://i.ibb.co/D4rDyfM/surprise.png')
+        elif emotion == 'neutral':
+            emoj = cv2.imread('https://i.ibb.co/KX7VSjh/neutral.png')
+        else:
+            emoj = cv2.imread('https://i.ibb.co/LdnS9nL/none.png')
+
+    # Adding Image on Screen
     # Read emoj and resize
     size = 150
     emoj = cv2.resize(emoj, (size, size))
@@ -47,27 +76,25 @@
     ret, mask = cv2.threshold(img2gray, 1, 255, cv2.THRESH_BINARY)
 
     roi = frame[-size-20:-20, -size-20:-20]
-    # roi = frame[-size-310:-310, -size-470:-470]
     # Set an index of where the mask is
     roi[np.where(mask)] = 0
     roi += emoj
 
-
-    #add text
+    # Add text
     font = cv2.FONT_HERSHEY_SIMPLEX
     org = (40, 210)
     fontScale = 1
     color = (255, 0, 0)
     thickness = 2
-    cv2.putText(frame,emotion, org, font, fontScale, color, thickness, cv2.LINE_AA)
-    
-    #show screen
-    cv2.imshow('frame',frame)
-    
-    #stop
+    cv2.putText(frame, emotion, org, font, fontScale, color, thickness, cv2.LINE_AA)
+
+    # Show screen
+    cv2.imshow('frame', frame)
+
+    # Stop
     if cv2.waitKey(1) & 0xff == ord('q'):
         break
 
+# Release resources
 scr.release()
-
-cv2.destroyAllWindows()
+cv2.destroyAllWindows()