aiData/Apps/YeLiTe/Test/test_cv.py

import sys
import os
import cv2
import numpy as np

# Add project root to path
project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
sys.path.append(project_root)

from Apps.YeLiTe.Kit import detect_cards_cv, read_image

def test_detection():
    image_path = r"d:\dsWork\aiData\Output\list_1768309287.jpg"
    if not os.path.exists(image_path):
        print(f"Error: Image not found at {image_path}")
        # Try to list files in Output to see what's available
        output_dir = os.path.dirname(image_path)
        if os.path.exists(output_dir):
            print(f"Files in {output_dir}:")
            for f in os.listdir(output_dir):
                print(f)
        return

    print(f"Testing detection on {image_path}")
    
    # Debug mode: copy logic from Kit.py but add debug prints and saves
    img = read_image(image_path)
    if img is None: return
    h, w = img.shape[:2]
    print(f"Image size: {w}x{h}")
    
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    blurred = cv2.GaussianBlur(gray, (5, 5), 0)
    
    # Try different thresholds
    edges = cv2.Canny(blurred, 10, 50) # Lower thresholds
    
    # Save edges
    debug_edges_path = os.path.join(os.path.dirname(__file__), "debug_edges.jpg")
    cv2.imencode('.jpg', edges)[1].tofile(debug_edges_path)
    print(f"Saved edges to {debug_edges_path}")
    
    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    print(f"Found {len(contours)} contours")
    
    # Draw all contours on a debug image
    debug_contours_img = img.copy()
    cv2.drawContours(debug_contours_img, contours, -1, (0, 0, 255), 1)
    debug_contours_path = os.path.join(os.path.dirname(__file__), "debug_contours.jpg")
    cv2.imencode('.jpg', debug_contours_img)[1].tofile(debug_contours_path)
    print(f"Saved all contours to {debug_contours_path}")

    min_card_width = int(w * 0.8)
    print(f"Min card width (strict): {min_card_width}")
    
    for i, cnt in enumerate(contours):
        x, y, cw, ch = cv2.boundingRect(cnt)
        if cw > 100 and ch > 50: # Only print somewhat large ones
            print(f"Contour {i}: pos=({x},{y}), size={cw}x{ch}, aspect_ratio={cw/ch:.2f}")

    # Run actual detection
    try:
        cards = detect_cards_cv(image_path)
        print(f"Detected {len(cards)} cards")
    except Exception as e:
        print(f"Error during detection: {e}")
        import traceback
        traceback.print_exc()
        return
    
    # Read image for drawing
    img_lv = read_image(image_path)
    img_flag = read_image(image_path)
    if img_lv is None:
        print("Failed to read image")
        return

    for i, card in enumerate(cards):
        x1, y1, x2, y2 = card
        print(f"Card {i+1}: [{x1}, {y1}, {x2}, {y2}]")
        
        # Draw green rectangle on img_lv
        cv2.rectangle(img_lv, (x1, y1), (x2, y2), (0, 255, 0), 2)
        cv2.putText(img_lv, f"Card {i+1}", (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
        
        # Calculate click point (center)
        center_x = (x1 + x2) // 2
        center_y = (y1 + y2) // 2
        
        # Draw red click point on img_flag
        cv2.circle(img_flag, (center_x, center_y), 5, (0, 0, 255), -1)
        # Also draw a crosshair for better visibility
        cv2.line(img_flag, (center_x - 10, center_y), (center_x + 10, center_y), (0, 0, 255), 1)
        cv2.line(img_flag, (center_x, center_y - 10), (center_x, center_y + 10), (0, 0, 255), 1)
        cv2.putText(img_flag, f"Click {i+1}", (center_x + 10, center_y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1)
        
        print(f"Click Point {i+1}: ({center_x}, {center_y})")

    # Save _lv.jpg
    base_name = os.path.splitext(os.path.basename(image_path))[0]
    output_lv = os.path.join(os.path.dirname(__file__), f"{base_name}_lv.jpg")
    cv2.imencode('.jpg', img_lv)[1].tofile(output_lv)
    print(f"Green box image saved to {output_lv}")

    # Save _flag.jpg
    output_flag = os.path.join(os.path.dirname(__file__), f"{base_name}_flag.jpg")
    cv2.imencode('.jpg', img_flag)[1].tofile(output_flag)
    print(f"Click point image saved to {output_flag}")

if __name__ == "__main__":
    test_detection()