| |
| """ |
| 演示可视化API功能的示例脚本 |
| 展示如何获取绘制了关键点和骨架的图像 |
| """ |
|
|
| import requests |
| import base64 |
| import json |
| import cv2 |
| import numpy as np |
| import time |
|
|
| def demo_api_usage(): |
| """演示API使用方法""" |
| |
| print("🎯 单鼠姿态检测可视化API演示") |
| print("=" * 50) |
| |
| |
| |
| image_path = "test_mouse.jpg" |
| |
| if not cv2.imread(image_path) is not None: |
| print("❌ 找不到测试图像，请确保test_mouse.jpg存在") |
| return |
| |
| |
| with open(image_path, "rb") as image_file: |
| image_base64 = base64.b64encode(image_file.read()).decode('utf-8') |
| |
| |
| request_data = { |
| "image": image_base64, |
| "conf_threshold": 0.3, |
| "frame_id": 1, |
| "timestamp": 1641234567.123, |
| "return_image": True, |
| "draw_bbox": False |
| } |
| |
| print("📤 发送API请求...") |
| print(f"请求参数: conf_threshold={request_data['conf_threshold']}") |
| print(f" return_image={request_data['return_image']}") |
| print(f" draw_bbox={request_data['draw_bbox']}") |
| |
| |
| api_url = "http://localhost:8765/api/process_frame" |
| |
| try: |
| start_time = time.time() |
| response = requests.post(api_url, json=request_data) |
| request_time = time.time() - start_time |
| |
| if response.status_code == 200: |
| result = response.json() |
| |
| print(f"✅ 请求成功！(耗时: {request_time:.3f}s)") |
| print("\n📊 检测结果:") |
| print(f" - 检测到小鼠: {result['mouse_detected']}") |
| |
| if result['mouse_detected']: |
| print(f" - 检测置信度: {result['confidence']:.3f}") |
| print(f" - 关键点数量: {len(result['keypoints'])}") |
| print(f" - 处理FPS: {result['fps']:.1f}") |
| |
| |
| print("\n🔍 检测到的关键点:") |
| for kpt in result['keypoints']: |
| print(f" {kpt['id']}: {kpt['name']} " |
| f"({kpt['x']:.1f}, {kpt['y']:.1f}) " |
| f"conf={kpt['confidence']:.3f}") |
| |
| |
| if "visualization_image" in result and result["visualization_image"]: |
| print("\n🎨 可视化图像处理:") |
| print(" ✅ 接收到绘制了关键点和骨架的图像") |
| |
| |
| img_bytes = base64.b64decode(result["visualization_image"]) |
| nparr = np.frombuffer(img_bytes, np.uint8) |
| vis_image = cv2.imdecode(nparr, cv2.IMREAD_COLOR) |
| |
| |
| output_path = "demo_visualization_result.jpg" |
| cv2.imwrite(output_path, vis_image) |
| |
| print(f" 💾 可视化图像已保存: {output_path}") |
| print(f" 📐 图像尺寸: {vis_image.shape}") |
| |
| |
| print(f" 📊 Base64数据大小: {len(result['visualization_image'])} 字符") |
| print(f" 📁 文件大小: {len(img_bytes)} 字节") |
| |
| else: |
| print("❌ 没有接收到可视化图像") |
| |
| print("\n" + "=" * 50) |
| print("🎉 演示完成！") |
| print("\n💡 使用说明:") |
| print(" 1. 设置 return_image=true 来获取可视化图像") |
| print(" 2. 设置 draw_bbox=false 只绘制关键点和骨架（如您所需）") |
| print(" 3. 设置 draw_bbox=true 同时绘制边界框") |
| print(" 4. 返回的 visualization_image 是Base64编码的JPEG图像") |
| |
| else: |
| print(f"❌ API请求失败: {response.status_code}") |
| print(f"错误信息: {response.text}") |
| |
| except Exception as e: |
| print(f"❌ 请求出错: {str(e)}") |
|
|
| def compare_with_without_visualization(): |
| """对比有无可视化的API响应""" |
| |
| print("\n" + "=" * 50) |
| print("🔄 对比测试：有无可视化图像的API响应") |
| print("=" * 50) |
| |
| |
| with open("test_mouse.jpg", "rb") as image_file: |
| image_base64 = base64.b64encode(image_file.read()).decode('utf-8') |
| |
| |
| configs = [ |
| { |
| "name": "不返回可视化图像", |
| "data": { |
| "image": image_base64, |
| "conf_threshold": 0.3, |
| "return_image": False |
| } |
| }, |
| { |
| "name": "返回可视化图像", |
| "data": { |
| "image": image_base64, |
| "conf_threshold": 0.3, |
| "return_image": True, |
| "draw_bbox": False |
| } |
| } |
| ] |
| |
| for config in configs: |
| print(f"\n📋 测试: {config['name']}") |
| |
| try: |
| response = requests.post("http://localhost:8765/api/process_frame", |
| json=config["data"]) |
| |
| if response.status_code == 200: |
| result = response.json() |
| |
| |
| response_size = len(response.content) |
| has_vis_image = "visualization_image" in result and result["visualization_image"] |
| |
| print(f" 📊 响应大小: {response_size:,} 字节") |
| print(f" 🖼️ 包含可视化图像: {'是' if has_vis_image else '否'}") |
| |
| if has_vis_image: |
| vis_size = len(result["visualization_image"]) |
| print(f" 📸 图像数据大小: {vis_size:,} 字符") |
| |
| print(f" ⚡ 处理时间: {result['processing_time']:.3f}s") |
| print(f" 🎯 检测结果: {'检测到小鼠' if result['mouse_detected'] else '未检测到小鼠'}") |
| |
| except Exception as e: |
| print(f" ❌ 测试失败: {str(e)}") |
|
|
| if __name__ == "__main__": |
| |
| try: |
| response = requests.get("http://localhost:8765/api/status", timeout=5) |
| if response.status_code != 200: |
| print("❌ WebRTC服务不可用，请先启动服务:") |
| print(" python gradio_webrtc_api.py") |
| exit(1) |
| except Exception: |
| print("❌ 无法连接到WebRTC服务，请先启动服务:") |
| print(" python gradio_webrtc_api.py") |
| exit(1) |
| |
| |
| demo_api_usage() |
| compare_with_without_visualization() |
