added readme to issue#165

Computer Vision/object detection by colour/readme.md

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+The code snippet sets up a basic color detection system using OpenCV's **Trackbars** to dynamically adjust the HSV (Hue, Saturation, and Value) values for detecting a specific color in real-time from a webcam feed.
+
+### Code Breakdown:
+
+1. **`nothing(x)` Function**: 
+   - This is a placeholder function for the trackbar callback. It doesn't need to perform any action, so it's left empty.
+
+2. **Creating Trackbars**:
+   - Six trackbars are created for adjusting the lower and upper limits of the HSV values.
+   - `L-H, L-S, L-V` trackbars adjust the lower bounds for hue, saturation, and value, while `U-H, U-S, U-V` adjust the upper bounds.
+
+3. **Video Capture**:
+   - The video stream is captured from the webcam using `cv2.VideoCapture(0)`. If you need to use an external camera or video feed, you can replace `0` with the camera index or video file path.
+
+4. **Main Loop**:
+   - The `while` loop continuously reads frames from the camera.
+   - It converts each frame from BGR to HSV color space (`cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)`) since HSV is more suitable for color segmentation.
+
+5. **HSV Value Adjustment**:
+   - The current positions of the trackbars are read using `cv2.getTrackbarPos()`, which allow the lower and upper HSV bounds to be adjusted in real-time.
+
+6. **Mask Creation**:
+   - `cv2.inRange()` creates a binary mask where the pixels within the HSV range (defined by the trackbar values) are white, and others are black.
+
+7. **Mask Application**:
+   - `cv2.bitwise_and()` applies the mask to the original frame to display only the pixels that fall within the selected color range.
+
+8. **Display**:
+   - The original frame (`frame`) and the result (`res`), which shows only the detected color, are displayed in separate windows.
+
+9. **Exit Condition**:
+   - The program will terminate when the `ESC` key (key code 27) is pressed.
+
+### Possible Enhancements:
+1. **Color Detection**:
+   - You can fine-tune the HSV values to detect a particular color (e.g., blue, red, green) by adjusting the trackbars in real-time.
+
+2. **Additional Displays**:
+   - Uncomment the `cv2.imshow('mask',mask)` line to also view the binary mask alongside the result.
+
+3. **Saving Settings**:
+   - You could add functionality to save the trackbar values once you have tuned them perfectly for a particular color, so they can be reused later without manually adjusting them every time.
+
+### Example Use Case:
+You could use this color detection method to track a colored object (e.g., a blue ball) in real-time by selecting the appropriate HSV range via the trackbars.