commit 6e882d2aa46a9484198a52b72a93a5a210922788 Author: 邓智航 <23373333@buaa.edu.cn> Date: Tue Dec 23 00:02:36 2025 +0800 first phrase diff --git a/reproject/__pycache__/analyzer.cpython-311.pyc b/reproject/__pycache__/analyzer.cpython-311.pyc new file mode 100644 index 0000000..67832eb Binary files /dev/null and b/reproject/__pycache__/analyzer.cpython-311.pyc differ diff --git a/reproject/__pycache__/emotion_test.cpython-311.pyc b/reproject/__pycache__/emotion_test.cpython-311.pyc new file mode 100644 index 0000000..eabf10e Binary files /dev/null and b/reproject/__pycache__/emotion_test.cpython-311.pyc differ diff --git a/reproject/__pycache__/face_library.cpython-311.pyc b/reproject/__pycache__/face_library.cpython-311.pyc new file mode 100644 index 0000000..4b5d87a Binary files /dev/null and b/reproject/__pycache__/face_library.cpython-311.pyc differ diff --git a/reproject/__pycache__/geometry_utils.cpython-311.pyc b/reproject/__pycache__/geometry_utils.cpython-311.pyc new file mode 100644 index 0000000..ba0e625 Binary files /dev/null and b/reproject/__pycache__/geometry_utils.cpython-311.pyc differ diff --git a/reproject/__pycache__/new_emotion_test.cpython-311.pyc b/reproject/__pycache__/new_emotion_test.cpython-311.pyc new file mode 100644 index 0000000..1054b19 Binary files /dev/null and b/reproject/__pycache__/new_emotion_test.cpython-311.pyc differ diff --git a/reproject/analyzer.py b/reproject/analyzer.py new file mode 100644 index 0000000..d0dc6c2 --- /dev/null +++ b/reproject/analyzer.py @@ -0,0 +1,173 @@ +import cv2 +import mediapipe as mp +import time +import numpy as np +from collections import deque +from geometry_utils import calculate_ear, calculate_mar_simple, estimate_head_pose, LEFT_EYE, RIGHT_EYE +from face_library import FaceLibrary + + +try: + from new_emotion_test import analyze_emotion_with_hsemotion + HAS_EMOTION_MODULE = True +except ImportError: + print("⚠️ 未找到 new_emotion_test.py，情绪功能将不可用") + HAS_EMOTION_MODULE = False + +class MonitorSystem: + def __init__(self, face_db): + # 初始化 MediaPipe + self.mp_face_mesh = mp.solutions.face_mesh + self.face_mesh = self.mp_face_mesh.FaceMesh( + max_num_faces=1, + refine_landmarks=True, + min_detection_confidence=0.5, + min_tracking_confidence=0.5 + ) + + # 初始化人脸底库 + self.face_lib = FaceLibrary(face_db) + + # 状态变量 + self.current_user = None + + # --- 时间控制 --- + self.last_identity_check_time = 0 + self.IDENTITY_CHECK_INTERVAL = 2.0 + + self.last_emotion_check_time = 0 + self.EMOTION_CHECK_INTERVAL = 3.0 + + # --- 历史数据 --- + self.HISTORY_LEN = 5 + self.ear_history = deque(maxlen=self.HISTORY_LEN) + self.mar_history = deque(maxlen=self.HISTORY_LEN) + + # 缓存上一次的检测结果 + self.cached_emotion = { + "label": "detecting...", + "va": (0.0, 0.0) + } + + def _get_smoothed_value(self, history, current_val): + """内部函数：计算滑动平均值""" + history.append(current_val) + if len(history) == 0: + return current_val + return sum(history) / len(history) + + def process_frame(self, frame): + """ + 输入 BGR 图像，返回分析结果字典 + """ + h, w = frame.shape[:2] + rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + + results = self.face_mesh.process(rgb_frame) + + analysis_data = { + "has_face": False, + "ear": 0.0, + "mar": 0.0, + "pose": (0, 0, 0), + "identity": self.current_user, + "emotion_label": self.cached_emotion["label"], + "emotion_va": self.cached_emotion["va"] + } + + if not results.multi_face_landmarks: + self.ear_history.clear() + self.mar_history.clear() + return analysis_data + + analysis_data["has_face"] = True + landmarks = results.multi_face_landmarks[0].landmark + + # 计算 EAR + left_ear = calculate_ear([landmarks[i] for i in LEFT_EYE], w, h) + right_ear = calculate_ear([landmarks[i] for i in RIGHT_EYE], w, h) + raw_ear = (left_ear + right_ear) / 2.0 + + # 计算 MAR + top = np.array([landmarks[13].x * w, landmarks[13].y * h]) + bottom = np.array([landmarks[14].x * w, landmarks[14].y * h]) + left = np.array([landmarks[78].x * w, landmarks[78].y * h]) + right = np.array([landmarks[308].x * w, landmarks[308].y * h]) + raw_mar = calculate_mar_simple(top, bottom, left, right) + + # --- 使用 History 进行数据平滑 --- + smoothed_ear = self._get_smoothed_value(self.ear_history, raw_ear) + smoothed_mar = self._get_smoothed_value(self.mar_history, raw_mar) + + # 计算头部姿态 + pitch, yaw, roll = estimate_head_pose(landmarks, w, h) + + analysis_data.update({ + "ear": round(smoothed_ear, 4), + "mar": round(smoothed_mar, 4), + "pose": (int(pitch), int(yaw), int(roll)) + }) + + now = time.time() + + # --- 身份识别 --- + if now - self.last_identity_check_time > self.IDENTITY_CHECK_INTERVAL: + xs = [l.x for l in landmarks] + ys = [l.y for l in landmarks] + # 计算人脸框 + face_loc = ( + int(min(ys) * h), int(max(xs) * w), + int(max(ys) * h), int(min(xs) * w) + ) + pad = 20 + face_loc = (max(0, face_loc[0]-pad), min(w, face_loc[1]+pad), + min(h, face_loc[2]+pad), max(0, face_loc[3]-pad)) + + match_result = self.face_lib.identify(rgb_frame, face_location=face_loc) + if match_result: + self.current_user = match_result["info"] + self.last_identity_check_time = now + + analysis_data["identity"] = self.current_user + + # --- 情绪识别 --- + if HAS_EMOTION_MODULE and (now - self.last_emotion_check_time > self.EMOTION_CHECK_INTERVAL): + if results.multi_face_landmarks: + landmarks = results.multi_face_landmarks[0].landmark + xs = [l.x for l in landmarks] + ys = [l.y for l in landmarks] + + # 计算裁剪坐标 + x_min = int(min(xs) * w) + x_max = int(max(xs) * w) + y_min = int(min(ys) * h) + y_max = int(max(ys) * h) + + pad_x = int((x_max - x_min) * 0.2) + pad_y = int((y_max - y_min) * 0.2) + + x_min = max(0, x_min - pad_x) + x_max = min(w, x_max + pad_x) + y_min = max(0, y_min - pad_y) + y_max = min(h, y_max + pad_y) + + face_crop = frame[y_min:y_max, x_min:x_max] + + if face_crop.size > 0: + try: + emo_results = analyze_emotion_with_hsemotion(face_crop) + + if emo_results: + top_res = emo_results[0] + self.cached_emotion["label"] = top_res.get("emotion", "unknown") + self.cached_emotion["va"] = top_res.get("vaVal", (0.0, 0.0)) + + except Exception as e: + print(f"情绪分析出错: {e}") + + self.last_emotion_check_time = now + + analysis_data["emotion_label"] = self.cached_emotion["label"] + analysis_data["emotion_va"] = self.cached_emotion["va"] + + return analysis_data \ No newline at end of file diff --git a/reproject/face_library.py b/reproject/face_library.py new file mode 100644 index 0000000..b882235 --- /dev/null +++ b/reproject/face_library.py @@ -0,0 +1,59 @@ +import face_recognition +import numpy as np + +class FaceLibrary: + def __init__(self, face_db): + """ + face_db: 字典 {"Name": {"image-path": "x.jpg", "age": 20}, ...} + """ + self.known_encodings = [] + self.known_names = [] + self.known_infos = [] + self._load_database(face_db) + + def _load_database(self, face_db): + print("正在加载人脸底库...") + for name, info in face_db.items(): + try: + image = face_recognition.load_image_file(info["image-path"]) + encodings = face_recognition.face_encodings(image) + if encodings: + self.known_encodings.append(encodings[0]) + self.known_names.append(name) + self.known_infos.append(info) + print(f"✅ 已加载: {name}") + else: + print(f"⚠️ 无法提取特征: {name}") + except Exception as e: + print(f"❌ 加载失败 {name}: {e}") + + def identify(self, frame_rgb, face_location=None, tolerance=0.5): + """ + frame_rgb: RGB 图片 + face_location: (top, right, bottom, left) 或者 None (全图搜索) + """ + if not self.known_encodings: + return None + + locations = [face_location] if face_location else None + + try: + encodings = face_recognition.face_encodings(frame_rgb, known_face_locations=locations) + + if not encodings: + return None + + unknown_encoding = encodings[0] + distances = face_recognition.face_distance(self.known_encodings, unknown_encoding) + min_idx = np.argmin(distances) + + if distances[min_idx] <= tolerance: + return { + "name": self.known_names[min_idx], + "info": self.known_infos[min_idx], + "distance": distances[min_idx] + } + except Exception as e: + print(f"识别出错: {e}") + + return None \ No newline at end of file diff --git a/reproject/geometry_utils.py b/reproject/geometry_utils.py new file mode 100644 index 0000000..403ad17 --- /dev/null +++ b/reproject/geometry_utils.py @@ -0,0 +1,94 @@ +import numpy as np +import cv2 + +# 左眼 +LEFT_EYE = [33, 160, 158, 133, 153, 144] +# 右眼 +RIGHT_EYE = [362, 385, 387, 263, 373, 380] +# 嘴唇 (内圈) +LIPS = [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308, 415, 310, 311, 312, 13] + +def _euclidean_distance(point1, point2): + return np.linalg.norm(point1 - point2) + +def calculate_ear(landmarks, width, height): + """计算眼睛纵横比 EAR""" + # 坐标转换 + points = np.array([(p.x * width, p.y * height) for p in landmarks]) + + # 垂直距离 + v1 = _euclidean_distance(points[1], points[5]) + v2 = _euclidean_distance(points[2], points[4]) + # 水平距离 + h = _euclidean_distance(points[0], points[3]) + + ear = (v1 + v2) / (2.0 * h) + return ear + +def calculate_mar(landmarks, width, height): + """计算嘴巴纵横比 MAR""" + points = np.array([(p.x * width, p.y * height) for p in landmarks]) + pass + +def calculate_mar_simple(top, bottom, left, right): + h = _euclidean_distance(top, bottom) + w = _euclidean_distance(left, right) + return h / w + +# geometry_utils.py 中的 estimate_head_pose 函数替换为以下内容 + +def estimate_head_pose(landmarks, width, height): + """ + 计算头部姿态 (Pitch, Yaw, Roll) + 返回单位：角度 (Degree) + """ + # 3D 模型点 (标准人脸模型) + model_points = np.array([ + (0.0, 0.0, 0.0), # Nose tip + (0.0, -330.0, -65.0), # Chin + (-225.0, 170.0, -135.0), # Left eye left corner + (225.0, 170.0, -135.0), # Right eye right corner + (-150.0, -150.0, -125.0), # Left Mouth corner + (150.0, -150.0, -125.0) # Right mouth corner + ]) + + # MediaPipe 对应的关键点索引 + idx_list = [1, 152, 33, 263, 61, 291] + + image_points = [] + for idx in idx_list: + p = landmarks[idx] + image_points.append((p.x * width, p.y * height)) + + image_points = np.array(image_points, dtype="double") + + focal_length = width + center = (width / 2, height / 2) + camera_matrix = np.array( + [[focal_length, 0, center[0]], + [0, focal_length, center[1]], + [0, 0, 1]], dtype="double" + ) + dist_coeffs = np.zeros((4, 1)) + + # 求解PnP + success, rotation_vector, translation_vector = cv2.solvePnP( + model_points, image_points, camera_matrix, dist_coeffs + ) + + rmat, _ = cv2.Rodrigues(rotation_vector) + angles, mtxR, mtxQ, Qx, Qy, Qz = cv2.RQDecomp3x3(rmat) + + pitch = angles[0] + yaw = angles[1] + roll = angles[2] + + if pitch < -180: pitch += 360 + if pitch > 180: pitch -= 360 + pitch = 180 - pitch if pitch > 0 else -pitch - 180 + if yaw < -180: yaw += 360 + if yaw > 180: yaw -= 360 + if roll < -180: roll += 360 + if roll > 180: roll -= 360 + + return pitch, yaw, roll \ No newline at end of file diff --git a/reproject/main.py b/reproject/main.py new file mode 100644 index 0000000..99aa199 --- /dev/null +++ b/reproject/main.py @@ -0,0 +1,286 @@ +import cv2 +import threading +import time +import queue +import socket +import json +import urllib.request +import struct +from analyzer import MonitorSystem + +SERVER_HOST = '10.128.50.6' +SERVER_PORT = 65432 +API_URL = "http://10.128.50.6:5000/api/states" +CAMERA_ID = "23373333" + +BASIC_FACE_DB = { + "Zhihang": {"name": "Zhihang Deng", "age": 20, "image-path": "zhihang.png"}, + "Yaoyu": {"name": "Yaoyu Zhang", "age": 20, "image-path": "yaoyu.jpg"}, +} + + +frame_queue = queue.Queue(maxsize=2) + +video_queue = queue.Queue(maxsize=1) + +data_queue = queue.Queue(maxsize=10) + +stop_event = threading.Event() + +def capture_thread(): + """ + 采集线程：优化了分发逻辑，对视频流进行降频处理 + """ + cap = cv2.VideoCapture(0) + cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640) + cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480) + + print("[Capture] 摄像头启动...") + + frame_count = 0 + + while not stop_event.is_set(): + ret, frame = cap.read() + if not ret: + break + + if not frame_queue.full(): + frame_queue.put(frame) + else: + try: + frame_queue.get_nowait() + frame_queue.put(frame) + except queue.Empty: + pass + + + if frame_count % 2 == 0: + try: + if video_queue.full(): + video_queue.get_nowait() + video_queue.put(frame) + except: + pass + + frame_count += 1 + time.sleep(0.01) + + cap.release() + print("[Capture] 线程结束") + +def analysis_thread(): + """ + 核心分析线程： + 1. 即使无人脸也发送状态（字段为空字符串）。 + 2. 队列满时丢弃旧数据，保证数据实时性。 + """ + monitor = MonitorSystem(BASIC_FACE_DB) + print("[Analysis] 分析系统启动...") + + while not stop_event.is_set(): + try: + frame = frame_queue.get(timeout=1) + except queue.Empty: + continue + + # 核心分析 + result = monitor.process_frame(frame) + + payload = { + "id": CAMERA_ID, + "time": time.strftime("%Y-%m-%d %H:%M:%S"), + "name": "", + "ear": "", + "mar": "", + "pose": "", + "emo_label": "", + "emo_va": "" + } + + if result["has_face"] and result["identity"]: + payload.update({ + "name": result["identity"]["name"], + "ear": result["ear"], + "mar": result["mar"], + "pose": result["pose"], + "emo_label": result["emotion_label"], + "emo_va": result["emotion_va"] + }) + elif result["has_face"]: + payload.update({ + "name": "Unknown", + "ear": result["ear"], + "mar": result["mar"], + "pose": result["pose"], + "emo_label": result["emotion_label"], + "emo_va": result["emotion_va"] + }) + + if data_queue.full(): + try: + _ = data_queue.get_nowait() + except queue.Empty: + pass + + data_queue.put(payload) + + draw_debug_info(frame, result) + cv2.imshow("Monitor Client", frame) + if cv2.waitKey(1) & 0xFF == ord('q'): + stop_event.set() + + cv2.destroyAllWindows() + print("[Analysis] 分析线程结束") + +def video_stream_thread(): + """ + 发送线程：优化了 Socket 设置和压缩参数 + """ + print(f"[Video] 准备连接服务器 {SERVER_HOST}:{SERVER_PORT} ...") + + while not stop_event.is_set(): + try: + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + s.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1) + + s.connect((SERVER_HOST, SERVER_PORT)) + print(f"[Video] 已连接") + + camera_id_bytes = CAMERA_ID.encode('utf-8') + + while not stop_event.is_set(): + try: + frame = video_queue.get(timeout=1) + + small_frame = cv2.resize(frame, (320, 240)) + + ret, buffer = cv2.imencode('.jpg', small_frame, [cv2.IMWRITE_JPEG_QUALITY, 50]) + + if not ret: continue + + frame_bytes = buffer.tobytes() + header_id_len = len(camera_id_bytes).to_bytes(4, 'big') + header_frame_len = len(frame_bytes).to_bytes(4, 'big') + + packet = header_id_len + camera_id_bytes + header_frame_len + frame_bytes + s.sendall(packet) + + except queue.Empty: + continue + except Exception as e: + print(f"[Video] 发送断开: {e}") + break + + except Exception as e: + print(f"[Video] 重连中... {e}") + time.sleep(3) + + print("[Video] 线程结束") + +def data_upload_thread(): + """ + 周期性爆发模式 + 逻辑：每隔 30 秒，连续发送 5 次数据（间隔 1 秒）。 + 由于 analysis_thread 保证了队列里总是最新数据，这里取到的就是实时状态。 + """ + print("[Data] 数据上报线程启动 (周期模式: 休眠30s -> 连发5次)") + + LONG_SLEEP = 30 + BURST_COUNT = 5 + BURST_GAP = 1 + + while not stop_event.is_set(): + # --- 阶段 1: 长休眠 (30秒) --- + if stop_event.wait(LONG_SLEEP): + break + + # --- 阶段 2: 爆发发送 (5次) --- + print(f"[Data] 开始上报周期 (连发 {BURST_COUNT} 次)...") + + try: + while not data_queue.empty(): + data_queue.get_nowait() + except queue.Empty: + pass + + time.sleep(0.1) + + for i in range(BURST_COUNT): + if stop_event.is_set(): + break + + try: + data = data_queue.get(timeout=1.5) + try: + req = urllib.request.Request( + url=API_URL, + data=json.dumps(data).encode('utf-8'), + headers={'Content-Type': 'application/json'}, + method='POST' + ) + with urllib.request.urlopen(req, timeout=2) as resp: + pass + + # 打印日志 + name_info = data['name'] if data['name'] else "NO-FACE" + print(f"[Data Upload {i+1}/{BURST_COUNT}] {name_info} | Time:{data['time']}") + + except Exception as e: + print(f"[Data] Upload Error: {e}") + + except queue.Empty: + print(f"[Data] 队列为空，跳过第 {i+1} 次发送") + + if i < BURST_COUNT - 1: + stop_event.wait(BURST_GAP) + + print("[Data] 数据上报线程结束") + +def draw_debug_info(frame, result): + """在画面上画出即时数据""" + if not result["has_face"]: + cv2.putText(frame, "NO FACE", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2) + return + + # 显示身份 + id_text = result["identity"]["name"] if result["identity"] else "Unknown" + color = (0, 255, 0) if result["identity"] else (0, 255, 255) + cv2.putText(frame, f"User: {id_text}", (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.7, color, 2) + + # 显示数据 + cv2.putText(frame, f"EAR: {result['ear']}", (20, 70), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 0), 1) + cv2.putText(frame, f"MAR: {result['mar']}", (20, 95), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 0), 1) + if result['ear'] < 0.15: + cv2.putText(frame, "EYE CLOSE", (250, 250), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2) + + p, y, r = result["pose"] + cv2.putText(frame, f"Pose: P{p} Y{y} R{r}", (20, 120), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 255), 1) + + emo = result.get("emotion_label", "N/A") + va = result.get("emotion_va", (0,0)) + # 显示格式: Emo: happy (-0.5, 0.2) + emo_text = f"Emo: {emo} ({va[0]:.2f}, {va[1]:.2f})" + cv2.putText(frame, emo_text, (20, 145), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 165, 255), 1) + +if __name__ == "__main__": + t1 = threading.Thread(target=capture_thread, daemon=True) + t2 = threading.Thread(target=analysis_thread, daemon=True) + t3 = threading.Thread(target=video_stream_thread, daemon=True) + t4 = threading.Thread(target=data_upload_thread, daemon=True) + + t1.start() + t2.start() + t3.start() + t4.start() + + try: + while not stop_event.is_set(): + time.sleep(1) + except KeyboardInterrupt: + print("停止程序...") + stop_event.set() + + t1.join() + t2.join() + t3.join() + t4.join() \ No newline at end of file diff --git a/reproject/new_emotion_test.py b/reproject/new_emotion_test.py new file mode 100644 index 0000000..52d46ad --- /dev/null +++ b/reproject/new_emotion_test.py @@ -0,0 +1,109 @@ +import cv2 +import numpy as np +import math +from hsemotion_onnx.facial_emotions import HSEmotionRecognizer + +EMOTION_VA_MAP = { + 'happy': (0.85, 0.60), + 'sad': (-0.75, -0.60), + 'angry': (-0.70, 0.80), + 'fear': (-0.65, 0.75), + 'surprise': (0.20, 0.85), + 'disgust': (-0.80, 0.40), + 'neutral': (0.00, 0.00), + 'contempt': (-0.60, 0.50), +} + +EMOTION_HANDLE = { + 'happiness': 'happy', + 'sadness': 'sad', + 'anger': 'angry', + 'fear': 'fear', + 'surprise': 'surprise', + 'disgust': 'disgust', + 'neutral': 'neutral', + 'contempt': 'contempt', +} + +def get_fine_grained_emotion(valence, arousal): + radius = math.sqrt(valence**2 + arousal**2) + angle = math.degrees(math.atan2(arousal, valence)) + + if radius < 0.25: + return "neutral" + + if 0 <= angle < 90: + if angle > 60: return "excited" + elif angle > 30: return "happy" + else: return "pleased" + elif 90 <= angle <= 180: + if angle > 150: return "nervous" + elif angle > 120: return "angry" + else: return "annoying" + elif -180 <= angle < -90: + if angle < -150: return "sad" + elif angle < -120: return "bored" + else: return "sleepy" + elif -90 <= angle < 0: + if angle < -60: return "calm" + elif angle < -30: return "peaceful" + else: return "relaxed" + + return "neutral" + +class EmotionAnalyzer: + def __init__(self): + print("正在加载 HSEmotion-ONNX 模型...") + self.fer = HSEmotionRecognizer(model_name='enet_b0_8_best_vgaf') + print("HSEmotion-ONNX 模型加载完成") + + def calculate_va_score(self, emotion_prob): + valence_sum = 0.0 + arousal_sum = 0.0 + total_prob = 0.0 + + for emotion, prob in emotion_prob.items(): + key = EMOTION_HANDLE.get(emotion.lower(), emotion.lower()) + if key in EMOTION_VA_MAP: + v, a = EMOTION_VA_MAP[key] + valence_sum += v * prob + arousal_sum += a * prob + total_prob += prob + + if total_prob == 0: + return 0.0, 0.0 + return valence_sum, arousal_sum + + def analyze(self, face_img_bgr): + if face_img_bgr is None or face_img_bgr.size == 0: + return [] + + face_img_rgb = cv2.cvtColor(face_img_bgr, cv2.COLOR_BGR2RGB) + + # predict_emotions 返回主要情绪标签和概率数组 + emotion_raw, scores = self.fer.predict_emotions(face_img_rgb, logits=False) + + probabilities = {} + for idx, score in enumerate(scores): + raw_label = self.fer.idx_to_class[idx] + key = EMOTION_HANDLE.get(raw_label.lower(), raw_label.lower()) + + probabilities[key] = float(score) + + valence, arousal = self.calculate_va_score(probabilities) + fine_grained_label = get_fine_grained_emotion(valence, arousal) + + result = { + "box": {}, + "vaVal": (round(valence, 4), round(arousal, 4)), + "probabilities": probabilities, + "dominant_emotion": EMOTION_HANDLE.get(emotion_raw.lower(), emotion_raw.lower()), + "emotion": fine_grained_label + } + + return [result] + +analyzer_instance = EmotionAnalyzer() + +def analyze_emotion_with_hsemotion(face_crop_bgr): + return analyzer_instance.analyze(face_crop_bgr) \ No newline at end of file diff --git a/reproject/requirement.txt b/reproject/requirement.txt new file mode 100644 index 0000000..7c467d8 Binary files /dev/null and b/reproject/requirement.txt differ diff --git a/reproject/va_reference.png b/reproject/va_reference.png new file mode 100644 index 0000000..f4c9923 Binary files /dev/null and b/reproject/va_reference.png differ diff --git a/reproject/yaoyu.jpg b/reproject/yaoyu.jpg new file mode 100644 index 0000000..a58aa39 Binary files /dev/null and b/reproject/yaoyu.jpg differ diff --git a/reproject/zhihang.png b/reproject/zhihang.png new file mode 100644 index 0000000..44ad9ec Binary files /dev/null and b/reproject/zhihang.png differ