Commit for Gitea

2026-04-28 12:14:58 +02:00
parent 225ecc2e17
commit a12182baa2
116 changed files with 2630 additions and 381 deletions
@@ -0,0 +1,188 @@
+import mediapipe as mp
+import cv2, numpy as np, time, fitz
+from helper import compute_distance
+from config import PINCH_THRESHOLD, RELEASE_THRESHOLD
+
+# hand_state.py
+from dataclasses import dataclass, field
+from typing import Tuple, Dict, Optional
+
+from helper import finger_straight
+
+# ----- Initialize Hand Detector -----
+mp_hands = mp.solutions.hands
+mp_draw  = mp.solutions.drawing_utils
+hands = mp_hands.Hands(
+    static_image_mode=False,
+    max_num_hands=8,
+    min_detection_confidence=0.7,
+    min_tracking_confidence=0.5
+)
+
+start_pt = None               # measurement start point
+measuring = False             # measurement in progress
+
+@dataclass
+class HandState:
+    id: int                              # a persistent identifier for this hand
+    landmarks: Dict[str, Tuple[int,int]] = field(default_factory=dict)
+    finger_straightness: Dict[str, float] = field(default_factory=dict)
+    gesture: Optional[str] = None        # e.g. "pinch", "fist", "open"
+    gesture_persistence: int = 0         # how many frames the current gesture has held
+
+#handList = Dict[int, HandState] = {}
+next_id = 0 
+
+def update(mp_results, frame_vis):
+    h, w, _ = frame_vis.shape
+    detected_centroids = []
+    landmarks_list     = []
+
+    # 1) pull out centroids & raw landmarks
+    if mp_results.multi_hand_landmarks:
+        for hand in mp_results.multi_hand_landmarks:
+            pts = []
+            for lm in hand.landmark:
+                pts.append((int(lm.x*w), int(lm.y*h)))
+            centroid = np.mean(pts, axis=0)
+            detected_centroids.append(tuple(centroid.astype(int)))
+            landmarks_list.append((hand, pts))
+
+    # 2) match to existing by nearest centroid
+    new_hands = {}
+    used_ids  = set()
+    for (hand, pts), centroid in zip(landmarks_list, detected_centroids):
+        # find best existing hand
+        best_id, best_dist = None, 1e9
+        for hid, state in handList.items():
+            dx, dy = np.array(state.landmarks['centroid']) - centroid
+            d = np.hypot(dx, dy)
+            if d < best_dist and d < 100:  # 100px max match distance
+                best_dist, best_id = d, hid
+
+        if best_id is None:
+            hid = next_id
+            next_id += 1
+            state = HandState(id=hid)
+        else:
+            hid   = best_id
+            state = handList[hid]
+
+        used_ids.add(hid)
+
+        # 3) update state
+        state.persistence += 1
+        state.landmarks['centroid'] = centroid
+
+        # compute fingertip positions
+        idx_tip = pts[mp.solutions.hands.HandLandmark.INDEX_FINGER_TIP]
+        mid_tip = pts[mp.solutions.hands.HandLandmark.MIDDLE_FINGER_TIP]
+        state.landmarks['index_tip']  = idx_tip
+        state.landmarks['middle_tip'] = mid_tip
+
+        for name, tip_i, pip_i, mcp_i in [
+            ('index', mp.solutions.hands.HandLandmark.INDEX_FINGER_TIP,
+                        mp.solutions.hands.HandLandmark.INDEX_FINGER_PIP,
+                        mp.solutions.hands.HandLandmark.INDEX_FINGER_MCP),
+            ('middle', mp.solutions.hands.HandLandmark.MIDDLE_FINGER_TIP,
+                        mp.solutions.hands.HandLandmark.MIDDLE_FINGER_PIP,
+                        mp.solutions.hands.HandLandmark.MIDDLE_FINGER_MCP),
+            # add ring, pinky, thumb similarly...
+        ]:
+            p_tip = pts[tip_i]
+            p_pip = pts[pip_i]
+            p_mcp = pts[mcp_i]
+            state.finger_straightness[name] = finger_straight(p_tip, p_pip, p_mcp)
+
+        # 5) simple gesture detection
+        if state.finger_straightness['index'] < 0.2 and \
+            state.finger_straightness['middle'] < 0.2:
+            gesture = 'fist'
+        elif state.finger_straightness['index'] > 0.8 and \
+                state.finger_straightness['middle'] > 0.8:
+            gesture = 'open'
+        else:
+            gesture = None
+
+        if gesture == state.gesture:
+            state.gesture_persistence += 1
+        else:
+            state.gesture = gesture
+            state.gesture_persistence = 0
+
+        new_hands[hid] = state
+
+    # 6) drop hands not seen this frame
+    handList = new_hands
+    return list(hands.values())
+
+
+
+def detect_hands(frame):
+    rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    rgb.flags.writeable = False
+    results = hands.process(rgb)    
+
+    return results
+
+
+def check_hand(hand, frame_vis, object_calibrating):
+    h, w, _ = frame_vis.shape
+
+    fingertip_idx = None
+    fingertip_mid = None
+    
+    mp_draw.draw_landmarks(frame_vis, hand, mp_hands.HAND_CONNECTIONS)
+    # get index and middle finger tips and PIP joints
+    idx_tip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
+    mid_tip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP]
+    ix, iy = int(idx_tip.x * w), int(idx_tip.y * h)
+    mx, my = int(mid_tip.x * w), int(mid_tip.y * h)
+    fingertip_idx = (ix, iy)
+    fingertip_mid = (mx, my)
+
+    # draw fingertips
+    cv2.circle(frame_vis, fingertip_idx, 8, (255,255,0), -1)
+    cv2.circle(frame_vis, fingertip_mid,  8, (0,255,0), -1)
+
+    measuring, start_pt = is_measuring(frame_vis, hand, object_calibrating)
+
+    return fingertip_idx, measuring, start_pt
+
+
+
+def is_measuring(frame_vis, hand, object_calibrating):
+    global measuring, start_pt
+    h, w, _ = frame_vis.shape
+
+    idx_tip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
+    idx_pip = hand.landmark[mp_hands.HandLandmark.INDEX_FINGER_PIP]
+    mid_tip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP]
+    mid_pip = hand.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_PIP]
+
+    ix, iy = int(idx_tip.x * w), int(idx_tip.y * h)
+    mx, my = int(mid_tip.x * w), int(mid_tip.y * h)
+    fingertip_idx = (ix, iy)
+    fingertip_mid = (mx, my)
+
+    # check extension
+    index_ext = idx_tip.y < idx_pip.y
+    middle_ext = mid_tip.y < mid_pip.y
+
+    # if measurement in progress but fingers no longer both extended, stop measuring
+    if measuring and not (index_ext and middle_ext):
+        measuring = False
+
+    # pinch distance
+    pinch = compute_distance(fingertip_idx, fingertip_mid)
+    cv2.putText(frame_vis, f"Pinch: {int(pinch)} px", (10,30), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,255,0),2)
+
+    # measurement gesture
+    if not object_calibrating and index_ext and middle_ext:
+        if pinch < PINCH_THRESHOLD and not measuring:
+            measuring = True
+            start_pt = fingertip_idx
+        elif pinch > RELEASE_THRESHOLD and measuring:
+            measuring = False
+
+    return measuring, start_pt