import requests
import cv2
import numpy as np
import os
import json
import argparse
import sys

# 配置服务地址
PYTHON_ALGO_URL = "http://192.168.0.37:18000"

def get_default_image_path():
    """获取一个默认存在的测试图片路径"""
    # 尝试找一个存在的真实图片
    potential_paths = [
        r"C:\Users\24830\Desktop\人脸.jpg",
    ]
    for path in potential_paths:
        if os.path.exists(path):
            return path
    return None

def detect_and_draw(image_path, expand_scale=0.0):
    url = f"{PYTHON_ALGO_URL}/api/detect_face"
    print(f"\n[Processing] Image: {image_path}")
    print(f"[API URL] {url}")
    print(f"[Expand Scale] {expand_scale}")
    
    if not os.path.exists(image_path):
        print(f"❌ Error: Image file not found: {image_path}")
        return

    try:
        # 1. 准备发送请求
        # 读取图片用于显示/画框
        img_array = np.fromfile(image_path, dtype=np.uint8)
        original_img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
        
        if original_img is None:
             print(f"❌ Error: Failed to read image using opencv: {image_path}")
             return

        # 2. 调用API
        data = {'expand_scale': expand_scale}
        with open(image_path, 'rb') as f:
            files = {'image': f}
            # 注意: 使用 data=data 发送表单数据，而不是 params=params (查询参数)
            response = requests.post(url, files=files, data=data, timeout=10)
        
        if response.status_code != 200:
            print(f"❌ Failed: Status {response.status_code}, Response: {response.text}")
            return

        result = response.json()
        print("\n=== API Response ===")
        print(json.dumps(result, indent=2))

        # 3. 处理结果并画图
        if result.get('success'):
            faces = result.get('faces', [])
            count = len(faces)
            print(f"\n✅ Success: Detected {count} faces.")
            
            # 创建副本用于画图
            draw_img = original_img.copy()

            for i, face in enumerate(faces):
                x1 = int(face['x1'])
                y1 = int(face['y1'])
                x2 = int(face['x2'])
                y2 = int(face['y2'])
                score = face['score']
                
                # 画矩形框
                # 颜色 (B, G, R) - 绿色
                color = (0, 255, 0)
                thickness = 2
                cv2.rectangle(draw_img, (x1, y1), (x2, y2), color, thickness)
                
                # 写文字
                label = f"Face {i+1}: {score:.2f}"
                cv2.putText(draw_img, label, (x1, y1 - 10), 
                           cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
                
                print(f"  - Face {i+1}: Box({x1}, {y1}, {x2}, {y2}), Score: {score:.4f}")

                # 保存裁剪的人脸图观察效果
                face_crop = original_img[y1:y2, x1:x2]
                if face_crop.size > 0:
                    crop_filename = f"face_crop_{i+1}_scale_{expand_scale}.jpg"
                    cv2.imencode('.jpg', face_crop)[1].tofile(crop_filename)
                    print(f"    Saved crop: {crop_filename}")

            # 4. 保存结果图
            output_filename = f"result_detected_scale_{expand_scale}.jpg"
            cv2.imencode('.jpg', draw_img)[1].tofile(output_filename)
            print(f"\n✅ Result image saved to: {os.path.abspath(output_filename)}")
            
        else:
            print(f"⚠️ API logic returned failure: {result.get('message')}") 

    except Exception as e:
        print(f"❌ Error: {e}")
        import traceback
        traceback.print_exc()

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Face Detection API Test Script')
    parser.add_argument('image_path', nargs='?', help='Path to the image file')
    parser.add_argument('--scale', type=float, default=0.6, help='Expand scale (default: 0.0)')
    
    args = parser.parse_args()
    
    target_path = args.image_path
    
    if not target_path:
        default_path = get_default_image_path()
        if default_path:
            print(f"No image path provided, using default found: {default_path}")
            target_path = default_path
        else:
            print("Usage: python test_detect_face.py <path_to_image> [--scale 0.3]")
            print("Error: No image path provided and no default test image found.")
            sys.exit(1)
            
    detect_and_draw(target_path, args.scale)