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import cv2
import numpy as np
from PIL import Image
class ImagePreprocessor:
def __init__(self, target_size=(224, 224)):
self.target_size = target_size
def preprocess_for_model(self, image):
"""
Final preprocessing for model input
"""
if isinstance(image, Image.Image):
image = np.array(image)
elif hasattr(image, 'cpu'): # Handle torch tensors
image = image.cpu().numpy()
# Ensure correct dtype
if image.dtype != np.uint8:
if image.max() <= 1.0:
image = (image * 255).astype(np.uint8)
else:
image = image.astype(np.uint8)
# Resize
image = cv2.resize(image, self.target_size)
# Normalize to [0,1]
image = image.astype(np.float32) / 255.0
return image
def combine_with_features(self, image, fertilizer_amount, days):
"""
Combine image with numerical features
"""
features = np.array([fertilizer_amount, days])
return image, features
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