results.py

import os
import cv2
import numpy as np
import matplotlib.pyplot as plt 
from PIL import Image

# Directory containing the inference results
inference_dir = '/home/agrosavia/Documents/rs_agrosavia/yolo_cocoa_2/runs/detect/train2'

# Collect all image paths with .png or .jpg extensions
paths2 = []
for dirname, _, filenames in os.walk(inference_dir):
    for filename in filenames:
        if filename.lower().endswith(('.png', '.jpg', '.jpeg')):
            paths2.append(os.path.join(dirname, filename))

paths2 = sorted(paths2)
print(f"Total images found: {len(paths2)}")
print("Sample image paths:", paths2[:3])

# Iterate through each image and display it
for path in paths2:
    try:
        # Open and convert the image to RGB (in case it's in a different mode)
        image = Image.open(path).convert('RGB')
        image_np = np.array(image)

        # Create a figure with specified size
        plt.figure(figsize=(20, 10))

        # Display the image
        plt.imshow(image_np)
        plt.axis('off')  # Hide axis for better visualization
        plt.title(os.path.basename(path), fontsize=15)  # Optional: Add image title

        # Show the plot
        plt.show()

    except Exception as e:
        print(f"Error loading image {path}: {e}")