127 lines
4.5 KiB
Python
127 lines
4.5 KiB
Python
import requests
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import cv2
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import numpy as np
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import os
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import json
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import argparse
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import sys
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# 配置服务地址
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PYTHON_ALGO_URL = "http://192.168.0.37:18000"
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def get_default_image_path():
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"""获取一个默认存在的测试图片路径"""
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# 尝试找一个存在的真实图片
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potential_paths = [
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r"C:\Users\24830\Desktop\人脸.jpg",
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]
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for path in potential_paths:
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if os.path.exists(path):
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return path
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return None
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def detect_and_draw(image_path, expand_scale=0.0):
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url = f"{PYTHON_ALGO_URL}/api/detect_face"
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print(f"\n[Processing] Image: {image_path}")
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print(f"[API URL] {url}")
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print(f"[Expand Scale] {expand_scale}")
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if not os.path.exists(image_path):
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print(f"❌ Error: Image file not found: {image_path}")
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return
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try:
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# 1. 准备发送请求
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# 读取图片用于显示/画框
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img_array = np.fromfile(image_path, dtype=np.uint8)
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original_img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
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if original_img is None:
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print(f"❌ Error: Failed to read image using opencv: {image_path}")
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return
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# 2. 调用API
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data = {'expand_scale': expand_scale}
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with open(image_path, 'rb') as f:
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files = {'image': f}
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# 注意: 使用 data=data 发送表单数据，而不是 params=params (查询参数)
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response = requests.post(url, files=files, data=data, timeout=10)
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if response.status_code != 200:
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print(f"❌ Failed: Status {response.status_code}, Response: {response.text}")
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return
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result = response.json()
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print("\n=== API Response ===")
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print(json.dumps(result, indent=2))
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# 3. 处理结果并画图
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if result.get('success'):
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faces = result.get('faces', [])
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count = len(faces)
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print(f"\n✅ Success: Detected {count} faces.")
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# 创建副本用于画图
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draw_img = original_img.copy()
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for i, face in enumerate(faces):
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x1 = int(face['x1'])
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y1 = int(face['y1'])
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x2 = int(face['x2'])
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y2 = int(face['y2'])
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score = face['score']
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# 画矩形框
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# 颜色 (B, G, R) - 绿色
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color = (0, 255, 0)
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thickness = 2
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cv2.rectangle(draw_img, (x1, y1), (x2, y2), color, thickness)
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# 写文字
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label = f"Face {i+1}: {score:.2f}"
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cv2.putText(draw_img, label, (x1, y1 - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
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print(f" - Face {i+1}: Box({x1}, {y1}, {x2}, {y2}), Score: {score:.4f}")
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# 保存裁剪的人脸图观察效果
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face_crop = original_img[y1:y2, x1:x2]
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if face_crop.size > 0:
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crop_filename = f"face_crop_{i+1}_scale_{expand_scale}.jpg"
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cv2.imencode('.jpg', face_crop)[1].tofile(crop_filename)
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print(f" Saved crop: {crop_filename}")
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# 4. 保存结果图
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output_filename = f"result_detected_scale_{expand_scale}.jpg"
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cv2.imencode('.jpg', draw_img)[1].tofile(output_filename)
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print(f"\n✅ Result image saved to: {os.path.abspath(output_filename)}")
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else:
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print(f"⚠️ API logic returned failure: {result.get('message')}")
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except Exception as e:
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print(f"❌ Error: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='Face Detection API Test Script')
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parser.add_argument('image_path', nargs='?', help='Path to the image file')
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parser.add_argument('--scale', type=float, default=0.6, help='Expand scale (default: 0.0)')
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args = parser.parse_args()
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target_path = args.image_path
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if not target_path:
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default_path = get_default_image_path()
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if default_path:
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print(f"No image path provided, using default found: {default_path}")
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target_path = default_path
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else:
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print("Usage: python test_detect_face.py <path_to_image> [--scale 0.3]")
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print("Error: No image path provided and no default test image found.")
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sys.exit(1)
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detect_and_draw(target_path, args.scale)
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