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app.py

@@ -0,0 +1,105 @@
+import streamlit as st
+import cv2
+import numpy as np
+import requests
+from gtts import gTTS
+import tempfile
+import pandas
+
+# ---------------- STREAMLIT CONFIG ----------------
+st.set_page_config(page_title="Hand2Voice", layout="wide")
+st.title("🤟 Hand2Voice")
+st.write("Hand Gesture to Voice Conversion")
+
+# ---------------- CONSTANTS ----------------
+GESTURE_URL = "https://raw.githubusercontent.com/imarshbir/Hand2Voice/main/gestures/gesture_rules.json"
+
+# ---------------- LOAD GESTURES ----------------
+@st.cache_data
+def load_gestures():
+    return requests.get(GESTURE_URL).json()["gestures"]
+
+# ---------------- LAZY MEDIAPIPE ----------------
+@st.cache_resource
+def load_mediapipe():
+    import mediapipe as mp
+    mp_hands = mp.solutions.hands
+    return mp_hands.Hands(
+        static_image_mode=True,
+        max_num_hands=1,
+        min_detection_confidence=0.7
+    )
+
+# ---------------- FINGER LOGIC ----------------
+def get_finger_states(hand_landmarks):
+    finger_tips = [4, 8, 12, 16, 20]
+    finger_bases = [2, 6, 10, 14, 18]
+
+    states = []
+
+    states.append(
+        1 if hand_landmarks.landmark[4].x >
+             hand_landmarks.landmark[3].x else 0
+    )
+
+    for tip, base in zip(finger_tips[1:], finger_bases[1:]):
+        states.append(
+            1 if hand_landmarks.landmark[tip].y <
+                 hand_landmarks.landmark[base].y else 0
+        )
+
+    return states
+
+# ---------------- MATCH GESTURE ----------------
+def match_gesture(states, rules):
+    for name, info in rules.items():
+        if states == info["pattern"]:
+            return name
+    return "Unknown Gesture"
+
+# ---------------- RECOGNITION ----------------
+def recognize_gesture(frame, hands, rules):
+    rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    result = hands.process(rgb)
+
+    if result.multi_hand_landmarks:
+        for hand_landmarks in result.multi_hand_landmarks:
+            states = get_finger_states(hand_landmarks)
+            return match_gesture(states, rules)
+
+    return "No Hand Detected"
+
+# ---------------- TEXT TO SPEECH ----------------
+def speak_text(text):
+    tts = gTTS(text=text, lang="en")
+    file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
+    tts.save(file.name)
+    return file.name
+
+# ---------------- UI ----------------
+col1, col2 = st.columns(2)
+
+with col1:
+    st.subheader("📷 Camera")
+    image = st.camera_input("Capture hand gesture")
+
+with col2:
+    st.subheader("📝 Output")
+
+    if image:
+        gestures = load_gestures()
+        hands = load_mediapipe()
+
+        img_bytes = image.getvalue()
+        img_array = np.frombuffer(img_bytes, np.uint8)
+        frame = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
+
+        gesture = recognize_gesture(frame, hands, gestures)
+
+        st.success(f"🔊 {gesture}")
+
+        if gesture not in ["Unknown Gesture", "No Hand Detected"]:
+            audio = speak_text(gesture)
+            st.audio(audio)
+    else:
+        st.info("Capture an image to start")

gesture_recognizer.py

@@ -0,0 +1,19 @@
+import cv2
+from hand_tracker import hands
+from gesture_logic import get_finger_states
+from gesture_matcher import match_gesture
+from gesture_loader import load_gestures
+
+gesture_rules = load_gestures()
+
+def recognize_gesture(frame):
+    rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    results = hands.process(rgb)
+
+    if results.multi_hand_landmarks:
+        for hand_landmarks in results.multi_hand_landmarks:
+            finger_states = get_finger_states(hand_landmarks)
+            gesture = match_gesture(finger_states, gesture_rules)
+            return gesture
+
+    return None

requirements.txt

@@ -1,3 +1,6 @@
-altair
-pandas
-streamlit
+streamlit
+opencv-python-headless
+mediapipe==0.10.9
+numpy
+requests
+gTTS