Delete app.py

app.py

@@ -1,57 +0,0 @@
-import gradio as gr
-import mediapipe as mp
-import cv2
-import numpy as np
-from PIL import Image
-from transformers import AutoTokenizer, AutoProcessor, AutoModelForVision2Seq
-
-model_id = "Qwen/Qwen2-VL-7B"
-
-tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
-processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
-model = AutoModelForVision2Seq.from_pretrained(
-    model_id, trust_remote_code=True, device_map="auto"
-).eval()
-
-mp_pose = mp.solutions.pose
-
-def analyze_posture_by_keypoints(landmarks):
-    left_shoulder = landmarks.landmark[11]
-    right_shoulder = landmarks.landmark[12]
-    left_ear = landmarks.landmark[7]
-    right_ear = landmarks.landmark[8]
-
-    shoulder_x = (left_shoulder.x + right_shoulder.x) / 2
-    ear_x = (left_ear.x + right_ear.x) / 2
-    delta = ear_x - shoulder_x
-    if abs(delta) > 0.06:
-        return "该用户存在驼背或低头倾向，头部明显前倾。"
-    else:
-        return "该用户坐姿较为端正，头部与肩部对齐。"
-
-def process(image: Image):
-    np_image = np.array(image)
-    with mp_pose.Pose(static_image_mode=True) as pose:
-        results = pose.process(cv2.cvtColor(np_image, cv2.COLOR_RGB2BGR))
-        if not results.pose_landmarks:
-            return "❗ 无法检测到人体，请上传包含上半身的清晰坐姿照片。"
-
-        posture_analysis = analyze_posture_by_keypoints(results.pose_landmarks)
-        prompt = f"请根据以下坐姿描述生成中英文提醒：\n{posture_analysis}"
-        inputs = processor(images=image, text=prompt, return_tensors="pt").to(model.device)
-        outputs = model.generate(**inputs, max_new_tokens=512)
-        result = tokenizer.decode(outputs[0], skip_special_tokens=True)
-        return result
-
-demo = gr.Interface(
-    fn=process,
-    inputs=gr.Image(type="pil", label="上传你的坐姿照片"),
-    outputs=gr.Textbox(label="中英文坐姿分析结果"),
-    title="🪑 Qwen2-VL 坐姿识别融合助手",
-    description="Mediapipe + Qwen2-VL 模型融合，上传图像判断是否驼背，并生成中英文提醒。",
-    theme="soft",
-    allow_flagging="never"
-)
-
-if __name__ == "__main__":
-    demo.launch()