├── requirements.txt
├── LICENSE
├── README.md
└── main.py


/requirements.txt:
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1 | opencv-python
2 | mediapipe
3 | numpy
4 | 


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/LICENSE:
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 1 | MIT License
 2 | 
 3 | Copyright (c) 2025 Tuba Khan
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


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/README.md:
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 1 | 
 2 | # Hand Tracking AR UI
 3 | 
 4 | This project is an Augmented Reality (AR) Hand Tracking User Interface demo. It uses Python, OpenCV, and MediaPipe to detect your hand via webcam and overlays futuristic UI graphics—radial gauges, HUD elements, and gesture-based controls—directly onto your hand in real time.
 5 | 
 6 | ## Features
 7 | - Real-time hand tracking using MediaPipe
 8 | - AR-style radial and pinch UI overlays
 9 | - Gesture-based switching (open hand, pinch, fist)
10 | - Futuristic HUD graphics: concentric circles, radial ticks, core pattern, numeric overlays
11 | - All graphics generated programmatically
12 | 
13 | ## Technologies Used
14 | - Python 3.8+
15 | - OpenCV
16 | - MediaPipe
17 | - Numpy
18 | 
19 | ## Installation
20 | 1. Clone this repository:
21 |    ```bash
22 |    git clone https://github.com/<your-username>/<your-repo>.git
23 |    cd <your-repo>
24 |    ```
25 | 2. Install dependencies:
26 |    ```bash
27 |    pip install -r requirements.txt
28 |    ```
29 | 3. Run the project:
30 |    ```bash
31 |    python main.py
32 |    ```
33 | 
34 | ## Usage
35 | - Allow webcam access when prompted.
36 | - Move your hand in front of the camera to interact with the AR UI overlays.
37 | - Try different gestures (open hand, pinch, fist) to see UI changes.
38 | 
39 | ## Author
40 | Made by Tuba Khan
41 | 
42 | ## License
43 | MIT License
44 | 


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/main.py:
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  1 | import cv2
  2 | import mediapipe as mp
  3 | import numpy as np
  4 | 
  5 | # Initialize MediaPipe Hands
  6 | mp_hands = mp.solutions.hands
  7 | mp_drawing = mp.solutions.drawing_utils
  8 | hands = mp_hands.Hands(static_image_mode=False,
  9 |                         max_num_hands=1,
 10 |                         min_detection_confidence=0.7,
 11 |                         min_tracking_confidence=0.7)
 12 | 
 13 | # Colors for UI overlays (reference style)
 14 | CYAN = (255, 255, 0)
 15 | ORANGE = (0, 180, 255)
 16 | WHITE = (255, 255, 255)
 17 | RED = (0, 0, 255)
 18 | CORE = (0, 255, 180)
 19 | 
 20 | def draw_glow_circle(img, center, radius, color, thickness=2, glow=15):
 21 |     # Draw outer glow
 22 |     for g in range(glow, 0, -3):
 23 |         alpha = 0.08 + 0.12 * (g / glow)
 24 |         overlay = img.copy()
 25 |         cv2.circle(overlay, center, radius+g, color, thickness)
 26 |         cv2.addWeighted(overlay, alpha, img, 1-alpha, 0, img)
 27 |     # Draw main circle
 28 |     cv2.circle(img, center, radius, color, thickness)
 29 | 
 30 | def draw_radial_ticks(img, center, radius, color, num_ticks=24, length=22, thickness=3):
 31 |     # Draw radial ticks (reference style)
 32 |     for i in range(num_ticks):
 33 |         angle = np.deg2rad(i * (360/num_ticks))
 34 |         x1 = int(center[0] + (radius-length) * np.cos(angle))
 35 |         y1 = int(center[1] + (radius-length) * np.sin(angle))
 36 |         x2 = int(center[0] + radius * np.cos(angle))
 37 |         y2 = int(center[1] + radius * np.sin(angle))
 38 |         cv2.line(img, (x1, y1), (x2, y2), color, thickness)
 39 | 
 40 | def draw_core_pattern(img, center, radius):
 41 |     # Draw stylized core (reference style)
 42 |     for t in np.linspace(0, 2*np.pi, 40):
 43 |         r = radius * (0.7 + 0.3 * np.sin(6*t))
 44 |         x = int(center[0] + r * np.cos(t))
 45 |         y = int(center[1] + r * np.sin(t))
 46 |         cv2.circle(img, (x, y), 3, ORANGE, -1)
 47 |     cv2.circle(img, center, int(radius*0.6), CYAN, 2)
 48 |     cv2.circle(img, center, int(radius*0.4), ORANGE, 2)
 49 | 
 50 | def draw_hud_details(img, center):
 51 |     # Draw bottom HUD bars and segments (reference style)
 52 |     for i in range(8):
 53 |         angle = np.deg2rad(210 + i*10)
 54 |         x1 = int(center[0] + 140 * np.cos(angle))
 55 |         y1 = int(center[1] + 140 * np.sin(angle))
 56 |         x2 = int(center[0] + 170 * np.cos(angle))
 57 |         y2 = int(center[1] + 170 * np.sin(angle))
 58 |         cv2.line(img, (x1, y1), (x2, y2), CYAN, 4)
 59 |     # Draw HUD blocks
 60 |     for i in range(4):
 61 |         angle = np.deg2rad(270 + i*15)
 62 |         x = int(center[0] + 120 * np.cos(angle))
 63 |         y = int(center[1] + 120 * np.sin(angle))
 64 |         cv2.rectangle(img, (x-10, y-10), (x+10, y+10), CYAN, 2)
 65 | 
 66 | def draw_arc_segments(img, center):
 67 |     # Draw arc segments (reference style)
 68 |     cv2.ellipse(img, center, (110,110), 0, -30, 210, CYAN, 3)
 69 |     cv2.ellipse(img, center, (100,100), 0, -30, 210, ORANGE, 2)
 70 |     cv2.ellipse(img, center, (80,80), 0, 0, 360, CYAN, 1)
 71 | 
 72 | # Start webcam
 73 | cap = cv2.VideoCapture(0)
 74 | 
 75 | while cap.isOpened():
 76 |     ret, frame = cap.read()
 77 |     if not ret:
 78 |         break
 79 |     frame = cv2.flip(frame, 1)
 80 |     rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
 81 |     results = hands.process(rgb)
 82 | 
 83 |     if results.multi_hand_landmarks:
 84 |         for hand_landmarks in results.multi_hand_landmarks:
 85 |             h, w, _ = frame.shape
 86 |             lm = [(int(l.x * w), int(l.y * h)) for l in hand_landmarks.landmark]
 87 | 
 88 |             # Draw hand skeleton
 89 |             mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
 90 | 
 91 |             palm = lm[9]
 92 |             tips = [lm[i] for i in [4, 8, 12, 16, 20]]
 93 |             dists = [np.linalg.norm(np.array(tip) - np.array(palm)) for tip in tips]
 94 |             avg_dist = np.mean(dists)
 95 | 
 96 |             # Pinch detection (thumb tip to index tip)
 97 |             pinch_dist = np.linalg.norm(np.array(lm[4]) - np.array(lm[8]))
 98 |             pinch_val = int(100 - min(pinch_dist, 100))
 99 | 
100 |             # Gesture logic
101 |             if avg_dist > 70:
102 |                 # Open hand: full AR UI
103 |                 draw_glow_circle(frame, palm, 120, CYAN, 3, glow=30)
104 |                 draw_glow_circle(frame, palm, 90, CYAN, 2, glow=20)
105 |                 draw_glow_circle(frame, palm, 60, ORANGE, 2, glow=10)
106 |                 draw_radial_ticks(frame, palm, 120, CYAN, num_ticks=24, length=22, thickness=3)
107 |                 draw_core_pattern(frame, palm, 35)
108 |                 draw_hud_details(frame, palm)
109 |                 draw_arc_segments(frame, palm)
110 |                 # Dynamic lines to fingertips
111 |                 for i in [4, 8, 12, 16, 20]:
112 |                     cv2.line(frame, palm, lm[i], CYAN, 2)
113 |                     cv2.circle(frame, lm[i], 12, ORANGE, -1)
114 |                 # Numeric overlay (angle between thumb and index)
115 |                 v1 = np.array(lm[4]) - np.array(palm)
116 |                 v2 = np.array(lm[8]) - np.array(palm)
117 |                 try:
118 |                     angle = int(np.degrees(np.arccos(np.dot(v1, v2)/(np.linalg.norm(v1)*np.linalg.norm(v2)+1e-6))))
119 |                 except:
120 |                     angle = 0
121 |                 cv2.putText(frame, f'{angle}°', (palm[0]+40, palm[1]-40), cv2.FONT_HERSHEY_DUPLEX, 1.5, WHITE, 4)
122 |             elif pinch_val < 60:
123 |                 # Pinch gesture: show orange arcs and value
124 |                 draw_glow_circle(frame, palm, 60, ORANGE, 3, glow=20)
125 |                 cv2.putText(frame, f'Pinch: {pinch_val}', (palm[0]-40, palm[1]-70), cv2.FONT_HERSHEY_SIMPLEX, 1, ORANGE, 3)
126 |                 for i in range(5):
127 |                     cv2.ellipse(frame, (palm[0]+80, palm[1]), (30,30), 0, 180, 180+pinch_val+i*10, ORANGE, 2)
128 |             else:
129 |                 # Fist: simple glowing circle
130 |                 draw_glow_circle(frame, palm, 60, CYAN, 3, glow=20)
131 |                 cv2.putText(frame, 'FIST', (palm[0]-30, palm[1]-70), cv2.FONT_HERSHEY_SIMPLEX, 1, ORANGE, 3)
132 | 
133 |     cv2.imshow('Hand Tracking AR UI', frame)
134 |     if cv2.waitKey(1) & 0xFF == 27:
135 |         break
136 | 
137 | cap.release()
138 | cv2.destroyAllWindows()
139 | cap.release()
140 | cv2.destroyAllWindows()
141 | 


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