Add/bicep reps

docs/projects/computer-vision/counting-bicep-reps.md

@@ -0,0 +1,160 @@
+# Counting Bicep Reps
+
+
+### AIM 
+To track and count bicep curls in real time using computer vision techniques with OpenCV and Mediapipe's Pose module.
+
+### DATASET LINK 
+This project does not use a specific dataset as it works with real-time video from a webcam.
+
+
+### NOTEBOOK LINK 
+[https://drive.google.com/file/d/13Omm8Zy0lmtjmdHgfQbraBu3NJf3wknw/view?usp=sharing](https://drive.google.com/file/d/13Omm8Zy0lmtjmdHgfQbraBu3NJf3wknw/view?usp=sharing)
+
+
+### LIBRARIES NEEDED
+
+??? quote "LIBRARIES USED"
+
+    - OpenCV
+    - Mediapipe
+    - NumPy
+
+--- 
+
+### DESCRIPTION 
+
+!!! info "What is the requirement of the project?"
+    - The project aims to provide a computer vision-based solution for tracking fitness exercises like bicep curls without the need for wearable devices or sensors. 
+
+??? info "Why is it necessary?"
+    - Helps fitness enthusiasts monitor their workouts in real time.
+    - Provides an affordable and accessible alternative to wearable fitness trackers.
+
+??? info "How is it beneficial and used?"
+    - Real-time feedback on workout form and repetition count.
+    - Can be extended to other fitness exercises and integrated into fitness apps
+
+??? info "How did you start approaching this project? (Initial thoughts and planning)"
+    - Explored Mediapipe's Pose module for pose landmark detection.
+    - Integrated OpenCV for video frame processing and real-time feedback.
+    - Planned the logic for detecting curls based on elbow angle thresholds.
+
+??? info "Mention any additional resources used (blogs, books, chapters, articles, research papers, etc.)."
+    - Mediapipe official documentation.
+    - OpenCV tutorials on video processing. 
+
+
+--- 
+
+### EXPLANATION 
+
+#### DETAILS OF THE DIFFERENT FEATURES 
+    - Pose Estimation: Utilized Mediapipe's Pose module to detect key landmarks on the human body.
+    - Angle Calculation: Calculated angles at the elbow joints to determine curl movement.
+    - Rep Tracking: Incremented rep count when alternating between full curl and relaxed positions.
+    - Real-Time Feedback: Displayed the remaining curl count on the video feed.
+
+
+--- 
+
+#### PROJECT WORKFLOW 
+
+=== "Step 1"
+    Initial setup:
+- Installed OpenCV and Mediapipe.
+- Set up a webcam feed for video capture.  
+
+
+=== "Step 2"
+    Pose detection:
+- Used Mediapipe's Pose module to identify body landmarks.
+
+
+=== "Step 3"
+    Angle calculation:
+- Implemented a function to calculate the angle between shoulder, elbow, and wrist.
+
+
+=== "Step 4"
+    Rep detection:
+- Monitored elbow angles to track upward and downward movements.
+
+
+=== "Step 5"
+    Real-time feedback:
+- Displayed the remaining number of curls on the video feed using OpenCV.
+
+
+=== "Step 6"
+    Completion:
+- Stopped the program when the target reps were completed or on manual exit.
+
+
+--- 
+
+#### PROJECT TRADE-OFFS AND SOLUTIONS 
+
+=== "Trade Off 1"
+    - Accuracy vs. Simplicity:
+        - Using elbow angles alone may not handle all body postures but ensures simplicity.
+        - Solution: Fine-tuned angle thresholds and added tracking for alternating arms.
+
+=== "Trade Off 2"
+    - Real-Time Performance vs. Model Complexity:
+        - Mediapipe's lightweight solution ensured smooth processing over heavier models.
+
+--- 
+
+### SCREENSHOTS 
+
+1. Entering no of reps you want to perform
+   ![Screenshot 2025-01-19 184454](https://github.com/user-attachments/assets/afac56f4-c0ce-45ec-8f41-1b7effc02e5a)
+
+
+3. Performing reps
+   ![Screenshot 2025-01-19 184607](https://github.com/user-attachments/assets/667b3e10-22b0-48a0-8e9b-42c3dcfc9f66)
+
+
+
+!!! success "Project workflow"
+
+    ```mermaid  
+    graph LR  
+    A[Webcam Feed] --> F[Enter No of Biceps Reps]
+    F --> B[Mediapipe Pose Detection]  
+    B --> C[Elbow Angle Calculation]  
+    C --> D[Rep Count Decrement]  
+    D --> E[Real-Time Update on Frsame]  
+    ```  
+
+--- 
+
+### CONCLUSION 
+
+#### KEY LEARNINGS 
+
+!!! tip "Insights gained from the data"
+    - Real-time video processing using OpenCV.
+    - Pose detection and landmark analysis with Mediapipe.
+
+??? tip "Improvements in understanding machine learning concepts"
+    - Understanding geometric computations in pose analysis.
+    - Effective use of pre-trained models like Mediapipe Pose.
+
+??? tip "Challenges faced and how they were overcome"
+    - Challenge: Handling incorrect postures.
+        - Solution: Fine-tuning angle thresholds.
+
+--- 
+
+#### USE CASES
+=== "Application 1"
+
+    **Personal Fitness Tracker**  
+    - Helps users track their workouts without additional equipment.  
+
+=== "Application 2"
+
+    **Fitness App Integration**  
+    - Can be integrated into fitness apps for real-time exercise tracking.  

docs/projects/computer-vision/index.md

@@ -12,4 +12,13 @@
   </div>
 </a>
 
+<!-- bicep reps counting -->
+<a href="counting-bicep-reps" style="padding: 0 2px 0 16px; background-color: rgba(39, 39, 43, 0.4); border: 1px solid rgba(76, 76, 82, 0.4); border-radius: 10px; box-shadow: 0 4px 8px rgba(0,0,0,0.1); overflow: hidden; transition: transform 0.2s; display: flex; align-items: center;">
+  <img src="https://www.researchgate.net/publication/368864097/figure/fig1/AS:11431281123465557@1677717597497/Mediapipe-Poses-position-detection-of-33-posture-joints-Mediapipe-has-many-functions.png" alt="OpenCV Logo" style="width: 300px; height: 150px; object-fit: cover; border-radius: 10px;" />
+  <div style="padding: 15px;">
+    <h2 style="margin: 0; font-size: 20px;">Counting Bicep Reps</h2>
+    <p style="font-size: 16px;">Real-time tracking and counting of bicep curls with Mediapipe's Pose module and OpenCV.</p>
+    <p style="font-size: 12px;">📅 2025-01-18 | ⏱️ 15 mins</p>
+  </div>
+</a>
 </div>