Add/brightness control

docs/projects/computer-vision/brightness-control.md

@@ -0,0 +1,186 @@
+# 📜 Brightness control  
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/59369441/116009572-1542a280-a638-11eb-9d94-2a2d38b856a5.PNG" />
+</div>
+
+## 🎯 AIM 
+To develop a real-time brightness control system using hand gestures, leveraging OpenCV and MediaPipe for hand detection and brightness adjustment.
+
+
+## 📊 DATASET LINK 
+No dataset used
+
+## 📓 NOTEBOOK LINK 
+<!-- Provide the link to the notebook where you solved the project. It must be only Kaggle public notebook link. -->
+[https://drive.google.com/file/d/1q7kraajGykfc2Kb6-84dCOjkrDGhIQcy/view?usp=sharing](https://drive.google.com/file/d/1q7kraajGykfc2Kb6-84dCOjkrDGhIQcy/view?usp=sharing)
+
+
+## ⚙️ TECH STACK
+
+| **Category**             | **Technologies**                            |
+|--------------------------|---------------------------------------------|
+| **Languages**            | Python                          |
+| **Libraries/Frameworks** | OpenCV, NumPy, MediaPipe, cvzone                    |
+| **Tools**                | Jupyter Notebook, Local Python IDE               |
+
+
+--- 
+
+## 📝 DESCRIPTION 
+!!! info "What is the requirement of the project?"
+    - The project requires a webcam to capture real-time video and detect hand gestures for brightness control.
+
+??? info "How is it beneficial and used?"
+     - Allows users to control screen brightness without physical touch, making it useful for touchless interfaces. 
+     - Ideal for applications in smart home systems and assistive technologies. 
+
+??? info "How did you start approaching this project? (Initial thoughts and planning)"
+    - Identified the need for a touchless brightness control system. 
+    - Selected OpenCV for video processing and MediaPipe for efficient hand tracking. 
+    - Developed a prototype to calculate brightness based on hand distance. 
+
+??? info "Mention any additional resources used (blogs, books, chapters, articles, research papers, etc.)."
+    - OpenCV documentation for video processing. 
+    - MediaPipe's official guide for hand tracking. 
+
+
+--- 
+
+## 🔍 EXPLANATION 
+
+### 🧩 DETAILS OF THE DIFFERENT FEATURES 
+
+#### 🛠 Developed Features 
+
+| Feature Name | Description | Reason   |
+|--------------|-------------|----------|
+| Hand Detection  | Detects hand gestures in real-time   | To control brightness with gestures |
+| Distance Calculation    | Calculates distance between fingers   | To adjust brightness dynamically |
+| Brightness Mapping    | Maps hand distance to brightness levels   | Ensures smooth adjustment of brightness |
+
+
+--- 
+
+### 🛤 PROJECT WORKFLOW 
+
+!!! success "Project workflow"
+
+    ``` mermaid
+      graph LR
+    A[Start] --> B[Initialize Webcam];
+    B --> C[Detect Hand Gestures];
+    C --> D[Calculate Distance];
+    D --> E[Adjust Brightness];
+    E --> F[Display Output];
+    ```
+
+=== "Step 1"
+- Initialize the webcam using OpenCV.
+
+
+=== "Step 2"
+- Use MediaPipe to detect hands in the video feed.
+
+=== "Step 3"
+- Calculate the distance between two fingers (e.g., thumb and index).
+
+=== "Step 4"
+- Map the distance to a brightness range.
+
+=== "Step 5"
+- Display the adjusted brightness on the video feed.
+
+--- 
+
+### 🖥 CODE EXPLANATION 
+
+=== "Section 1: Webcam Initialization" 
+- The program begins by setting up the webcam to capture frames with a resolution of 640x480 pixels. This ensures consistent processing and visualization of the video stream.
+
+    ```python
+    cap = cv2.VideoCapture(0)  
+    cap.set(3, 640)  # Set width  
+    cap.set(4, 480)  # Set height 
+    ```
+
+=== "Section 2: Hand Detection and Brightness Control" 
+- Using the `HandDetector` from `cvzone`, the program tracks one hand (maxHands=1). The brightness of the video frame is dynamically adjusted based on the distance between the thumb and index finger.
+
+    ```python
+    detector = HandDetector(detectionCon=0.8, maxHands=1)  
+    brightness = 1.0  # Default brightness level  
+    ```
+
+- The HandDetector detects hand landmarks in each frame with a confidence threshold of 0.8. The initial brightness is set to 1.0 (normal).
+
+    ```python
+    hands, img = detector.findHands(frame, flipType=False)  
+
+    if hands:  
+        hand = hands[0]  
+        lm_list = hand['lmList']  
+        if len(lm_list) > 8:  
+            thumb_tip = lm_list[4]  
+            index_tip = lm_list[8]  
+            distance = int(((thumb_tip[0] - index_tip[0]) ** 2 + (thumb_tip[1] - index_tip[1]) ** 2) ** 0.5)  
+            brightness = np.interp(distance, [20, 200], [0, 1])  
+    ```
+
+- The program calculates the distance between the thumb tip (`lmList[4]`) and index finger tip (`lmList[8]`). This distance is mapped to a brightness range of 0 to 1 using np.interp.
+
+=== "Section 3: Brightness Adjustment and Display " 
+
+- The captured frame's brightness is modified by scaling the value (V) channel in the HSV color space according to the calculated brightness level.
+
+    ```python
+    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)  
+    hsv[..., 2] = np.clip(hsv[..., 2] * brightness, 0, 255).astype(np.uint8)  
+    frame_bright = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)  
+    cv2.imshow("Brightness Controller", frame_bright)  
+    ```
+
+- This technique ensures smooth, real-time brightness adjustments based on the user's hand gestures. The output frame is displayed with the adjusted brightness level.
+
+
+--- 
+
+### ⚖️ PROJECT TRADE-OFFS AND SOLUTIONS 
+
+
+=== "Trade Off 1" 
+    - Real-time processing vs. computational efficiency: Optimized hand detection by limiting the maximum number of detectable hands to 1.
+
+
+=== "Trade Off 2" 
+    - Precision in brightness control vs. usability: Adjusted mapping function to ensure smooth transitions.
+
+--- 
+
+## 🖼 SCREENSHOTS 
+??? tip "Working of the model"
+
+    === "Image Topic"
+    <img width="485" alt="image" src="https://github.com/user-attachments/assets/4b7ea465-a916-4592-9026-9bfa41711763" />
+
+
+
+--- 
+
+## ✅ CONCLUSION 
+
+### 🔑 KEY LEARNINGS 
+!!! tip "Insights gained from the data" 
+- Improved understanding of real-time video processing. 
+- Learned to integrate gesture detection with hardware functionalities.
+
+??? tip "Improvements in understanding machine learning concepts" 
+- Gained insights into MediaPipe's efficient hand detection algorithms.
+
+--- 
+
+### 🌍 USE CASES
+=== "Smart Homes" 
+- Touchless brightness control for smart home displays.
+
+=== "Assistive Technologies" 
+- Brightness adjustment for users with limited mobility.

docs/projects/computer-vision/index.md

@@ -21,4 +21,14 @@
     <p style="font-size: 12px;">📅 2025-01-18 | ⏱️ 15 mins</p>
   </div>
 </a>
+
+<!-- brightness control using opencv and mediapipe -->
+<a href="brightness-control" 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://user-images.githubusercontent.com/59369441/116009572-1542a280-a638-11eb-9d94-2a2d38b856a5.PNG" alt="MediaPipe Hand Tracking" style="width: 300px; height: 150px; object-fit: cover; border-radius: 10px;" />
+  <div style="padding: 15px;">
+    <h2 style="margin: 0; font-size: 20px;">Brightness Control</h2>
+    <p style="font-size: 16px;">Adjust screen brightness dynamically using MediaPipe's Hand Tracking and OpenCV.</p>
+    <p style="font-size: 12px;">📅 2025-01-24 | ⏱️ 10 mins</p>
+  </div>
+</a>
 </div>