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from typing import Literal, Type, TYPE_CHECKING, Union | |
import cv2 | |
import numpy as np | |
from PIL import Image, ImageOps | |
Step: Type = Literal['caption', 'caption_short', 'create_mask', 'contrast_stretch'] | |
img_manipulation_steps = ['contrast_stretch'] | |
img_ext = ['.jpg', '.jpeg', '.png', '.webp'] | |
if TYPE_CHECKING: | |
from .llava_utils import LLaVAImageProcessor | |
from .fuyu_utils import FuyuImageProcessor | |
ImageProcessor = Union['LLaVAImageProcessor', 'FuyuImageProcessor'] | |
def pil_to_cv2(image): | |
"""Convert a PIL image to a cv2 image.""" | |
return cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR) | |
def cv2_to_pil(image): | |
"""Convert a cv2 image to a PIL image.""" | |
return Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) | |
def load_image(img_path: str): | |
image = Image.open(img_path).convert('RGB') | |
try: | |
# transpose with exif data | |
image = ImageOps.exif_transpose(image) | |
except Exception as e: | |
pass | |
return image | |
def resize_to_max(image, max_width=1024, max_height=1024): | |
width, height = image.size | |
if width <= max_width and height <= max_height: | |
return image | |
scale = min(max_width / width, max_height / height) | |
width = int(width * scale) | |
height = int(height * scale) | |
return image.resize((width, height), Image.LANCZOS) | |