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# -*- coding: utf-8 -*-
import os
import re
import ftfy
import torch
import html
from PIL import Image
from transformers import CLIPProcessor, CLIPModel, CLIPTokenizer, CLIPTextModel
class CLIPEmbedder:
"""
A class for embedding texts and images using a pretrained CLIP model.
"""
def __init__(self, device='cuda', model_name='openai/clip-vit-base-patch32', cache_dir='./cache_dir', use_text_preprocessing=True, max_length=77):
"""
Initializes the CLIPEmbedder with specified model and configurations.
"""
self.device = torch.device(device)
self.model_name = model_name
self.cache_dir = cache_dir
self.use_text_preprocessing = use_text_preprocessing
self.max_length = max_length
os.makedirs(self.cache_dir, exist_ok=True)
self.processor = CLIPProcessor.from_pretrained(model_name, cache_dir=self.cache_dir)
self.model = CLIPModel.from_pretrained(model_name, cache_dir=self.cache_dir).to(self.device).eval()
self.tokenizer = CLIPTokenizer.from_pretrained(model_name)
self.text_model = CLIPTextModel.from_pretrained(model_name, cache_dir=self.cache_dir).to(self.device).eval()
for param in self.text_model.parameters():
param.requires_grad = False
def get_text_embeddings(self, texts):
"""
Generates embeddings for a list of text prompts.
"""
self._validate_input_list(texts, str)
if self.use_text_preprocessing:
texts = [self._clean_text(text) for text in texts]
inputs = self.processor(text=texts, return_tensors="pt", padding=True, truncation=True, max_length=self.max_length).to(self.device)
with torch.no_grad():
embeddings = self.model.get_text_features(**inputs)
return embeddings
def encode_text(self, texts):
"""
Encodes texts into embeddings and returns the last hidden state and pooled output.
"""
self._validate_input_list(texts, str)
batch_encoding = self.tokenizer(texts, return_tensors="pt", truncation=True, max_length=self.max_length, padding="max_length").to(self.device)
with torch.no_grad():
outputs = self.text_model(**batch_encoding)
return outputs.last_hidden_state, outputs.pooler_output
def get_image_embeddings(self, image_paths):
"""
Generates embeddings for a list of image file paths.
"""
self._validate_input_list(image_paths, str)
images = [self._load_image(path) for path in image_paths]
inputs = self.processor(images=images, return_tensors="pt").to(self.device)
with torch.no_grad():
embeddings = self.model.get_image_features(**inputs)
return embeddings
def _validate_input_list(self, input_list, expected_type):
"""
Validates that the input is a list of expected type.
"""
if not isinstance(input_list, list) or not all(isinstance(item, expected_type) for item in input_list):
raise ValueError(f"Input must be a list of {expected_type.__name__}.")
def _clean_text(self, text):
"""
Applies basic cleaning and formatting to a text string.
"""
text = ftfy.fix_text(text)
text = html.unescape(text)
return text.strip()
def _load_image(self, image_path):
"""
Loads and preprocesses an image from a file path.
"""
try:
image = Image.open(image_path).convert("RGB")
except FileNotFoundError:
raise FileNotFoundError(f"Image file not found: {image_path}")
except Exception as e:
raise Exception(f"Error loading image {image_path}: {e}")
return image
def clean_caption(self, caption):
caption = str(caption)
caption = ul.unquote_plus(caption)
caption = caption.strip().lower()
caption = re.sub('<person>', 'person', caption)
# urls:
caption = re.sub(
r'\b((?:https?:(?:\/{1,3}|[a-zA-Z0-9%])|[a-zA-Z0-9.\-]+[.](?:com|co|ru|net|org|edu|gov|it)[\w/-]*\b\/?(?!@)))', # noqa
'', caption) # regex for urls
caption = re.sub(
r'\b((?:www:(?:\/{1,3}|[a-zA-Z0-9%])|[a-zA-Z0-9.\-]+[.](?:com|co|ru|net|org|edu|gov|it)[\w/-]*\b\/?(?!@)))', # noqa
'', caption) # regex for urls
caption = BeautifulSoup(caption, features='html.parser').text
caption = re.sub(r'@[\w\d]+\b', '', caption)
caption = re.sub(r'[\u31c0-\u31ef]+', '', caption)
caption = re.sub(r'[\u31f0-\u31ff]+', '', caption)
caption = re.sub(r'[\u3200-\u32ff]+', '', caption)
caption = re.sub(r'[\u3300-\u33ff]+', '', caption)
caption = re.sub(r'[\u3400-\u4dbf]+', '', caption)
caption = re.sub(r'[\u4dc0-\u4dff]+', '', caption)
caption = re.sub(r'[\u4e00-\u9fff]+', '', caption)
caption = re.sub(
r'[\u002D\u058A\u05BE\u1400\u1806\u2010-\u2015\u2E17\u2E1A\u2E3A\u2E3B\u2E40\u301C\u3030\u30A0\uFE31\uFE32\uFE58\uFE63\uFF0D]+', # noqa
'-', caption)
caption = re.sub(r'[`´«»“”¨]', '"', caption)
caption = re.sub(r'[‘’]', "'", caption)
caption = re.sub(r'"?', '', caption)
caption = re.sub(r'&', '', caption)
caption = re.sub(r'\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}', ' ', caption)
caption = re.sub(r'\d:\d\d\s+$', '', caption)
caption = re.sub(r'\\n', ' ', caption)
caption = re.sub(r'#\d{1,3}\b', '', caption)
caption = re.sub(r'#\d{5,}\b', '', caption)
caption = re.sub(r'\b\d{6,}\b', '', caption)
caption = re.sub(r'[\S]+\.(?:png|jpg|jpeg|bmp|webp|eps|pdf|apk|mp4)', '', caption)
caption = re.sub(r'[\"\']{2,}', r'"', caption)
caption = re.sub(r'[\.]{2,}', r' ', caption)
caption = re.sub(self.bad_punct_regex, r' ', caption)
caption = re.sub(r'\s+\.\s+', r' ', caption)
regex2 = re.compile(r'(?:\-|\_)')
if len(re.findall(regex2, caption)) > 3:
caption = re.sub(regex2, ' ', caption)
caption = self.basic_clean(caption)
caption = re.sub(r'\b[a-zA-Z]{1,3}\d{3,15}\b', '', caption) # jc6640
caption = re.sub(r'\b[a-zA-Z]+\d+[a-zA-Z]+\b', '', caption) # jc6640vc
caption = re.sub(r'\b\d+[a-zA-Z]+\d+\b', '', caption) # 6640vc231
caption = re.sub(r'(worldwide\s+)?(free\s+)?shipping', '', caption)
caption = re.sub(r'(free\s)?download(\sfree)?', '', caption)
caption = re.sub(r'\bclick\b\s(?:for|on)\s\w+', '', caption)
caption = re.sub(r'\b(?:png|jpg|jpeg|bmp|webp|eps|pdf|apk|mp4)(\simage[s]?)?', '', caption)
caption = re.sub(r'\bpage\s+\d+\b', '', caption)
caption = re.sub(r'\b\d*[a-zA-Z]+\d+[a-zA-Z]+\d+[a-zA-Z\d]*\b', r' ', caption) # j2d1a2a...
caption = re.sub(r'\b\d+\.?\d*[xх×]\d+\.?\d*\b', '', caption)
caption = re.sub(r'\b\s+\:\s+', r': ', caption)
caption = re.sub(r'(\D[,\./])\b', r'\1 ', caption)
caption = re.sub(r'\s+', ' ', caption)
caption.strip()
caption = re.sub(r'^[\"\']([\w\W]+)[\"\']$', r'\1', caption)
caption = re.sub(r'^[\'\_,\-\:;]', r'', caption)
caption = re.sub(r'[\'\_,\-\:\-\+]$', r'', caption)
caption = re.sub(r'^\.\S+$', '', caption)
return caption.strip()
@staticmethod
def basic_clean(text):
text = ftfy.fix_text(text)
text = html.unescape(html.unescape(text))
return text.strip()
if __name__ == '__main__':
clip_embedder = CLIPEmbedder()
# Example
text_prompts = [
'A photo of a cute puppy playing with a ball.',
'An image of a beautiful sunset over the ocean.',
'A scene depicting a busy city street.'
]
text_embeddings = clip_embedder.get_text_embeddings(text_prompts)
print(f"Text embeddings shape: {text_embeddings.shape}")
image_paths = ['image1.jpg', 'image2.png']
try:
image_embeddings = clip_embedder.get_image_embeddings(image_paths)
print(f"Image embeddings shape: {image_embeddings.shape}")
except FileNotFoundError as e:
print(e)
except Exception as e:
print(f"An error occurred: {e}")
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