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import gradio as gr | |
import numpy as np, cv2, io, base64 | |
import librosa, joblib | |
from deepface import DeepFace | |
# 预加载模型 | |
audio_model = joblib.load("voice_model.joblib") | |
# 人脸情绪分析函数 | |
def analyze_face(frame): | |
# frame: H×W×3 numpy array, RGB | |
try: | |
res = DeepFace.analyze(frame, actions=['emotion'], enforce_detection=False) | |
return res['dominant_emotion'] | |
except Exception as e: | |
return f"Error: {e}" | |
# 语音情绪分析函数 | |
def analyze_audio(wav_file): | |
if wav_file is None: return "no audio" | |
data = wav_file.read() | |
y, sr = librosa.load(io.BytesIO(data), sr=None) | |
mfccs = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13) | |
feat = np.mean(mfccs.T, axis=0) | |
pred = audio_model.predict([feat])[0] | |
return pred | |
# 文本情绪分析函数 | |
def analyze_text(txt): | |
if not txt: return "no text" | |
mapping = { | |
"😊 happy": ["開心","快樂","愉快","喜悅","歡喜","興奮","高興","歡"], | |
"😠 angry": ["生氣","憤怒","不爽","發火","火大","氣憤"], | |
"😢 sad": ["傷心","難過","哭","憂","悲","心酸","哀","痛苦","慘","愁"], | |
"😲 surprise":["驚訝","意外","嚇","好奇","驚詫","詫異","訝異"], | |
"😨 fear": ["怕","恐懼","緊張","懼","膽怯","畏"], | |
} | |
for emo, kw in mapping.items(): | |
if any(w in txt for w in kw): | |
return emo | |
return "neutral" | |
# Gradio 界面 | |
with gr.Blocks() as demo: | |
gr.Markdown("# 多模態即時情緒分析") | |
with gr.Tabs(): | |
with gr.TabItem("📷 即時人臉"): | |
camera = gr.Camera(label="請對準鏡頭") | |
face_out = gr.Textbox(label="偵測到的情緒") | |
camera.change(analyze_face, inputs=camera, outputs=face_out) | |
with gr.TabItem("🎤 上傳語音"): | |
audio = gr.Audio(source="upload", type="file", label="上傳 WAV") | |
audio_out = gr.Textbox(label="語音情緒") | |
audio.change(analyze_audio, inputs=audio, outputs=audio_out) | |
with gr.TabItem("⌨️ 輸入文字"): | |
txt_input = gr.Textbox(label="輸入文字") | |
txt_btn = gr.Button("分析文字") | |
txt_out = gr.Textbox(label="文字情緒") | |
txt_btn.click(analyze_text, inputs=txt_input, outputs=txt_out) | |
gr.Markdown( | |
"⚠️ Hugging Face Spaces 無法直接呼叫本機攝影機;" | |
"請在手機/電腦瀏覽器使用,或拉到最下方打開 Camera 頁籤測試。" | |
) | |
if __name__ == "__main__": | |
demo.launch() |