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import torch
import numpy as np
from PIL import Image
from typing import Tuple, Optional, Union
import torchvision.transforms as transforms
class ImageProcessorManager:
"""Image validation, preprocessing and format standardization"""
def __init__(self):
self.supported_formats = ['JPEG', 'PNG', 'WEBP', 'JPG']
self.min_resolution = (224, 224)
# CLIP preprocessing transform
self.clip_transform = transforms.Compose([
transforms.Resize((336, 336), interpolation=transforms.InterpolationMode.BICUBIC),
transforms.ToTensor(),
transforms.Normalize(
mean=[0.48145466, 0.4578275, 0.40821073],
std=[0.26862954, 0.26130258, 0.27577711]
)
])
def load_image(self, file_path: Union[str, Image.Image]) -> Image.Image:
"""Load and validate image"""
if isinstance(file_path, Image.Image):
image = file_path
else:
try:
image = Image.open(file_path)
except Exception as e:
raise ValueError(f"Failed to load image: {e}")
# Convert to RGB
if image.mode != 'RGB':
image = image.convert('RGB')
# Check resolution
if image.size[0] < self.min_resolution[0] or image.size[1] < self.min_resolution[1]:
raise ValueError(f"Image resolution too low, minimum required: {self.min_resolution}")
return image
def preprocess_for_yolo(self, image: Image.Image) -> np.ndarray:
"""Preprocess image for YOLO (keep original format)"""
return np.array(image)
def preprocess_for_clip(self, image: Image.Image) -> torch.Tensor:
"""Preprocess image for CLIP (336x336, ImageNet normalization)"""
return self.clip_transform(image)
def preprocess_for_qwen(self, image: Image.Image) -> Image.Image:
"""Preprocess image for Qwen2.5-VL (dynamic resolution)"""
return image
def resize_with_aspect_ratio(self, image: Image.Image, max_size: int = 1024) -> Image.Image:
"""Resize image while maintaining aspect ratio"""
width, height = image.size
if max(width, height) > max_size:
if width > height:
new_width = max_size
new_height = int(height * (max_size / width))
else:
new_height = max_size
new_width = int(width * (max_size / height))
image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
return image
print("✓ ImageProcessorManager defined")
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