| |
| |
| import re |
| import numpy as np |
| import time |
| import random |
| from typing import List, Dict, Any, Tuple, Optional, Union |
| from math import sqrt |
| import io |
| import os |
| import json |
|
|
| import requests |
| from PIL import Image, ImageFile |
|
|
| import betterproto |
|
|
| try: |
| from .utils.lens_betterproto import * |
| except ImportError: |
| try: |
| from .utils.lens_betterproto import * |
| except ImportError: |
| raise ImportError( |
| "Could not import lens_betterproto. " |
| "Make sure lens_betterproto.py exists." |
| ) from None |
|
|
| try: |
| from .base import register_OCR, OCRBase, TextBlock |
| except ImportError: |
|
|
| class OCRBase: |
| def __init__(self, **params): |
| self.params = params |
| self.debug_mode = int(os.environ.get("OCR_DEBUG", 0)) |
| |
| import logging |
|
|
| self.logger = logging.getLogger(__name__) |
| if not self.logger.hasHandlers(): |
| handler = logging.StreamHandler() |
| formatter = logging.Formatter( |
| "[%(levelname)-5s] %(name)s:%(funcName)s:%(lineno)d - %(message)s" |
| ) |
| handler.setFormatter(formatter) |
| self.logger.addHandler(handler) |
| self.logger.setLevel(logging.DEBUG if self.debug_mode else logging.INFO) |
| self.logger.info( |
| "Running Lens_OCR_exp without .base module. Using placeholder classes." |
| ) |
|
|
| def get_param_value(self, key): |
| return self.params.get(key) |
|
|
| def updateParam(self, key, value): |
| self.params[key] = value |
|
|
| def register_OCR(name): |
| return lambda cls: cls |
|
|
| class TextBlock: |
| def __init__(self): |
| self.xyxy = (0, 0, 0, 0) |
| self.text = "" |
|
|
|
|
| ImageFile.LOAD_TRUNCATED_IMAGES = True |
|
|
| try: |
| import fpng_py |
|
|
| OPTIMIZED_PNG_ENCODE = True |
| except ImportError: |
| OPTIMIZED_PNG_ENCODE = False |
|
|
|
|
| def _pil_image_to_bytes( |
| img: Image.Image, |
| img_format="png", |
| png_compression=6, |
| jpeg_quality=80, |
| optimize=False, |
| ) -> bytes: |
| """Converts PIL Image object to bytes of the specified format.""" |
| if img_format == "png" and OPTIMIZED_PNG_ENCODE and not optimize: |
| try: |
| rgba_img = img.convert("RGBA") |
| raw_data = rgba_img.tobytes() |
| image_bytes = fpng_py.fpng_encode_image_to_memory( |
| raw_data, img.width, img.height |
| ) |
| return image_bytes |
| except Exception: |
| pass |
|
|
| image_bytes_io = io.BytesIO() |
| save_kwargs = {} |
| img_to_save = img |
| if img_format == "jpeg": |
| if img.mode == "RGBA" or (img.mode == "P" and "transparency" in img.info): |
| background = Image.new("RGB", img.size, (255, 255, 255)) |
| try: |
| background.paste(img, mask=img.split()[3]) |
| except IndexError: |
| background.paste(img) |
| img_to_save = background |
| elif img.mode != "RGB": |
| img_to_save = img.convert("RGB") |
|
|
| save_kwargs["quality"] = jpeg_quality |
| save_kwargs["subsampling"] = 0 |
| save_kwargs["optimize"] = optimize |
| elif img_format == "png": |
| save_kwargs["compress_level"] = png_compression |
| save_kwargs["optimize"] = optimize |
|
|
| img_to_save.save(image_bytes_io, format=img_format.upper(), **save_kwargs) |
| return image_bytes_io.getvalue() |
|
|
|
|
| def _preprocess_image_for_lens(img: Image.Image) -> Tuple[Optional[bytes], int, int]: |
| """Prepares image for Google Lens Protobuf API.""" |
| try: |
| original_width, original_height = img.size |
| max_pixels = 3_000_000 |
| if original_width * original_height > max_pixels: |
| aspect_ratio = original_width / original_height |
| new_w = int(sqrt(max_pixels * aspect_ratio)) |
| new_h = int(new_w / aspect_ratio) |
| img_to_process = ( |
| img.resize((new_w, new_h), Image.Resampling.LANCZOS) |
| if new_w > 0 and new_h > 0 |
| else img |
| ) |
| else: |
| img_to_process = img |
|
|
| img_bytes = _pil_image_to_bytes(img_to_process, img_format="png") |
| return (img_bytes, img_to_process.width, img_to_process.height) |
| except Exception as e: |
| |
| print(f"ERROR: Image preprocessing failed: {e}") |
| return (None, 0, 0) |
|
|
|
|
| @register_OCR("google_lens_exp") |
| class OCRLensAPI_exp(OCRBase): |
| """ |
| OCR using the experimental Google Lens Protobuf API (using requests). |
| Requires 'betterproto', 'requests', and 'lens_betterproto.py'. |
| """ |
|
|
| params = { |
| "delay": 1.5, |
| "newline_handling": { |
| "type": "selector", |
| "options": ["preserve", "remove"], |
| "value": "preserve", |
| "description": "Handle newline characters in the final OCR string.", |
| }, |
| "no_uppercase": { |
| "type": "checkbox", |
| "value": False, |
| "description": "Convert text to lowercase except first letter of sentences.", |
| }, |
| "target_language": { |
| "value": "ja", |
| "description": "Target language code (e.g., 'ja', 'en', 'ru').", |
| }, |
| "proxy": { |
| "value": "", |
| "description": 'Proxy (requests format: e.g., http://user:pass@host:port or {"http": ..., "https": ...})', |
| }, |
| "description": "OCR using Google Lens Protobuf API (requests backend)", |
| } |
|
|
| @property |
| def request_delay(self) -> float: |
| delay_val = self.get_param_value("delay") |
| try: |
| return max(0.0, float(delay_val)) |
| except (ValueError, TypeError, AttributeError): |
| return 1.0 |
|
|
| @property |
| def newline_handling(self) -> str: |
| handling = self.get_param_value("newline_handling") |
| return handling if handling in ["preserve", "remove"] else "preserve" |
|
|
| @property |
| def no_uppercase(self) -> bool: |
| no_upper = self.get_param_value("no_uppercase") |
| return bool(no_upper) if no_upper is not None else False |
|
|
| @property |
| def target_language(self) -> str: |
| lang = self.get_param_value("target_language") |
| return lang if isinstance(lang, str) and len(lang) >= 2 else "ja" |
|
|
| @property |
| def proxy(self) -> Optional[Dict[str, str]]: |
| val = self.get_param_value("proxy") |
| proxies_dict = None |
| if isinstance(val, str) and val.strip().startswith("{"): |
| try: |
| parsed_dict = json.loads(val) |
| if isinstance(parsed_dict, dict): |
| proxies_dict = {} |
| |
| http_key = next( |
| ( |
| k |
| for k in parsed_dict |
| if k.lower() == "http" or k.lower() == "http://" |
| ), |
| None, |
| ) |
| https_key = next( |
| ( |
| k |
| for k in parsed_dict |
| if k.lower() == "https" or k.lower() == "https://" |
| ), |
| None, |
| ) |
| if http_key: |
| proxies_dict["http"] = parsed_dict[http_key] |
| if https_key: |
| proxies_dict["https"] = parsed_dict[https_key] |
| return proxies_dict if proxies_dict else None |
| except Exception: |
| if val.strip(): |
| proxies_dict = {"http": val.strip(), "https": val.strip()} |
| else: |
| return None |
| elif isinstance(val, str) and val.strip(): |
| proxies_dict = {"http": val.strip(), "https": val.strip()} |
| elif isinstance(val, dict) and val: |
| |
| proxies_dict = val |
|
|
| return proxies_dict if proxies_dict else None |
|
|
| def __init__(self, **params) -> None: |
| super().__init__(**params) |
| self.last_request_time: float = 0 |
| self._api_url = "https://lensfrontend-pa.googleapis.com/v1/crupload" |
| self._api_key = "AIzaSyDr2UxVnv_U85AbhhY8XSHSIavUW0DC-sY" |
| self._api_headers = { |
| "Host": "lensfrontend-pa.googleapis.com", |
| "Connection": "keep-alive", |
| "Content-Type": "application/x-protobuf", |
| "X-Goog-Api-Key": self._api_key, |
| "Sec-Fetch-Site": "none", |
| "Sec-Fetch-Mode": "no-cors", |
| "Sec-Fetch-Dest": "empty", |
| "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36", |
| "Accept-Encoding": "gzip, deflate, br", |
| "Accept-Language": "en-US,en;q=0.9", |
| } |
|
|
| def _prepare_protobuf_request( |
| self, image_bytes: bytes, width: int, height: int |
| ) -> Optional[bytes]: |
| """Creates and serializes the Protobuf request.""" |
| try: |
| request = LensOverlayServerRequest() |
| req_id = request.objects_request.request_context.request_id |
| client_ctx = request.objects_request.request_context.client_context |
| locale_ctx = client_ctx.locale_context |
| img_data = request.objects_request.image_data |
|
|
| req_id.uuid = random.randint(0, 2**64 - 1) |
| req_id.sequence_id = 1 |
| req_id.image_sequence_id = 1 |
| req_id.analytics_id = random.randbytes(16) |
|
|
| client_ctx.platform = Platform.WEB |
| client_ctx.surface = Surface.CHROMIUM |
| locale_ctx.language = self.target_language |
| locale_ctx.region = "JP" |
| locale_ctx.time_zone = "Asia/Tokyo" |
|
|
| filter_obj = AppliedFilter(filter_type=LensOverlayFilterType.AUTO_FILTER) |
| client_ctx.client_filters.filter.append(filter_obj) |
|
|
| img_data.payload.image_bytes = image_bytes |
| img_data.image_metadata.width = width |
| img_data.image_metadata.height = height |
|
|
| return bytes(request) |
| except Exception as e: |
| self.logger.error( |
| f"Failed to prepare Protobuf request: {e}", exc_info=self.debug_mode |
| ) |
| return None |
|
|
| def _parse_protobuf_response( |
| self, response_proto: LensOverlayServerResponse |
| ) -> str: |
| """Extracts text from Protobuf response, ignoring non-critical error Type=0.""" |
| extracted_text = "" |
| has_error_type_0 = False |
|
|
| try: |
| if response_proto.error: |
| err_type = response_proto.error.error_type |
| if ( |
| err_type != LensOverlayServerErrorErrorType.UNKNOWN_TYPE |
| ): |
| error_type_name = LensOverlayServerErrorErrorType(err_type).name |
| self.logger.error( |
| f"Lens server returned critical error: Type={err_type} ({error_type_name})" |
| ) |
| return "" |
| else: |
| self.logger.debug( |
| "Lens server returned non-critical error: Type=0 (UNKNOWN_TYPE)." |
| " Attempting to extract text anyway." |
| ) |
| has_error_type_0 = True |
|
|
| text_layout = getattr( |
| getattr(response_proto, "objects_response", None), "text", None |
| ) |
| paragraphs = getattr( |
| getattr(text_layout, "text_layout", None), "paragraphs", None |
| ) |
|
|
| if paragraphs: |
| paragraph_texts = [] |
| for paragraph in paragraphs: |
| para_text_builder = io.StringIO() |
| for line in getattr(paragraph, "lines", []): |
| for word in getattr(line, "words", []): |
| para_text_builder.write(getattr(word, "plain_text", "")) |
| separator = getattr(word, "text_separator", None) |
| if separator is not None: |
| para_text_builder.write(separator) |
| paragraph_texts.append(para_text_builder.getvalue()) |
| para_text_builder.close() |
| extracted_text = "".join(paragraph_texts).strip() |
| extracted_text = re.sub(r"\s+", " ", extracted_text).strip() |
|
|
| if self.debug_mode and has_error_type_0: |
| self.logger.debug( |
| "Successfully extracted text despite non-critical error Type=0." |
| ) |
|
|
| elif not has_error_type_0: |
| if self.debug_mode: |
| self.logger.debug( |
| "Text layout not found in Protobuf structure (and no error reported)." |
| ) |
|
|
| except Exception as e: |
| self.logger.error( |
| f"Failed to parse Protobuf response structure: {e}", |
| exc_info=self.debug_mode, |
| ) |
| return "" |
|
|
| return extracted_text |
|
|
| def _execute_ocr_request( |
| self, image_bytes: bytes, width: int, height: int |
| ) -> Optional[LensOverlayServerResponse]: |
| """Sends prepared request via requests and returns deserialized response.""" |
| payload = self._prepare_protobuf_request(image_bytes, width, height) |
| if not payload: |
| return None |
|
|
| self._respect_delay() |
| response_proto = None |
| session = requests.Session() |
|
|
| current_proxy = self.proxy |
| if current_proxy: |
| session.proxies = current_proxy |
| if self.debug_mode: |
| self.logger.debug( |
| f"Using requests proxy configuration: {current_proxy}" |
| ) |
|
|
| |
| skip_ssl_verify = os.environ.get("OCR_SKIP_SSL_VERIFY", "false").lower() in ( |
| "true", |
| "1", |
| "yes", |
| ) |
| ssl_verify = not skip_ssl_verify |
|
|
| try: |
| if self.debug_mode: |
| self.logger.debug( |
| f"Sending Protobuf request ({len(payload)} bytes) via requests " |
| f"to lens api (SSL Verify: {ssl_verify})" |
| ) |
|
|
| response = session.post( |
| self._api_url, |
| data=payload, |
| headers=self._api_headers, |
| timeout=(10.0, 30.0), |
| verify=ssl_verify, |
| ) |
| self.last_request_time = time.time() |
|
|
| if self.debug_mode: |
| self.logger.debug( |
| f"Received requests response status: {response.status_code}" |
| ) |
|
|
| response.raise_for_status() |
|
|
| response_proto = LensOverlayServerResponse().parse(response.content) |
| if self.debug_mode: |
| self.logger.debug("Protobuf response parsed successfully (requests).") |
|
|
| except requests.exceptions.SSLError as e: |
| self.logger.error( |
| f"SSL Error connecting to Lens API (requests): {e}. " |
| f"If using a proxy or corporate network, check its configuration. " |
| f"You might need to trust a custom CA or set OCR_SKIP_SSL_VERIFY=true (unsafe).", |
| exc_info=self.debug_mode, |
| ) |
| except requests.exceptions.HTTPError as e: |
| response_text = getattr(e.response, "text", "N/A")[:500] |
| self.logger.error( |
| f"HTTP error from Lens API (requests): {e.response.status_code}. " |
| f"Response: {response_text}", |
| exc_info=self.debug_mode, |
| ) |
| except requests.exceptions.RequestException as e: |
| self.logger.error( |
| f"Request error connecting to Lens API (requests): {e}", |
| exc_info=self.debug_mode, |
| ) |
| except (betterproto.Error, ValueError, TypeError) as e: |
| self.logger.error( |
| f"Failed to parse Protobuf response (requests): {e}", |
| exc_info=self.debug_mode, |
| ) |
| if "response" in locals() and hasattr(response, "content"): |
| self.logger.debug( |
| f"Raw response content (first 500 bytes): {response.content[:500]}" |
| ) |
| except Exception as e: |
| self.logger.error( |
| f"Unexpected error during OCR request (requests): {e}", |
| exc_info=self.debug_mode, |
| ) |
| finally: |
| session.close() |
|
|
| return response_proto |
|
|
| def ocr(self, img: np.ndarray) -> str: |
| """Main OCR method for a single image (numpy array).""" |
| if self.debug_mode > 1: |
| self.logger.debug( |
| f"Starting OCR (Lens Protobuf / requests) on image shape: {img.shape}" |
| ) |
| if img is None or img.size == 0: |
| if self.debug_mode: |
| self.logger.warning("Empty image provided") |
| return "" |
|
|
| full_text = "" |
| try: |
| pil_img = Image.fromarray(img) |
| processed_bytes, width, height = _preprocess_image_for_lens(pil_img) |
|
|
| if not processed_bytes: |
| self.logger.error("Image preprocessing failed.") |
| return "" |
| if self.debug_mode > 1: |
| self.logger.debug( |
| f"Preprocessed image: {width}x{height}, {len(processed_bytes)} bytes" |
| ) |
|
|
| response_proto = self._execute_ocr_request(processed_bytes, width, height) |
|
|
| if response_proto: |
| full_text = self._parse_protobuf_response(response_proto) |
| if self.debug_mode and full_text: |
| self.logger.debug(f"Parsed text preview: '{full_text[:100]}...'") |
|
|
| if self.newline_handling == "remove": |
| full_text = re.sub(r"\s+", " ", full_text).strip() |
| full_text = self._apply_punctuation_and_spacing(full_text) |
| if self.no_uppercase: |
| full_text = self._apply_no_uppercase(full_text) |
| else: |
| self.logger.warning( |
| "OCR request did not return a valid response object." |
| ) |
|
|
| except Exception as e: |
| self.logger.error( |
| f"Unexpected error in OCR process: {e}", exc_info=self.debug_mode |
| ) |
| return "" |
|
|
| return str(full_text) if full_text is not None else "" |
|
|
| def ocr_img(self, img: np.ndarray) -> str: |
| if self.debug_mode > 1: |
| self.logger.debug(f"ocr_img shape: {img.shape}") |
| return self.ocr(img) |
|
|
| def _ocr_blk_list( |
| self, img: np.ndarray, blk_list: List[TextBlock], *args, **kwargs |
| ): |
| """Processes a list of text blocks on the image.""" |
| im_h, im_w = img.shape[:2] |
| if self.debug_mode: |
| self.logger.debug( |
| f"Image size: {im_h}x{im_w}. Processing {len(blk_list)} blocks." |
| ) |
| for i, blk in enumerate(blk_list): |
| x1, y1, x2, y2 = blk.xyxy |
| if self.debug_mode > 1: |
| self.logger.debug( |
| f"Processing block {i+1}/{len(blk_list)}: ({x1, y1, x2, y2})" |
| ) |
|
|
| y1c, y2c = max(0, y1), min(im_h, y2) |
| x1c, x2c = max(0, x1), min(im_w, x2) |
|
|
| if y1c < y2c and x1c < x2c: |
| try: |
| cropped_img = img[y1c:y2c, x1c:x2c] |
| if cropped_img.size > 0: |
| blk.text = self.ocr(cropped_img) |
| else: |
| if self.debug_mode: |
| self.logger.warning(f"Empty cropped image for block {i+1}.") |
| blk.text = "" |
| except Exception as crop_err: |
| self.logger.error( |
| f"Error cropping/processing block {i+1}: {crop_err}", |
| exc_info=self.debug_mode, |
| ) |
| blk.text = "" |
| else: |
| if self.debug_mode: |
| self.logger.warning( |
| f"Invalid/zero-area bbox {blk.xyxy} (clamped: {x1c,y1c,x2c,y2c})" |
| ) |
| blk.text = "" |
|
|
| def _apply_no_uppercase(self, text: str) -> str: |
| """Applies lowercase except for first letter of sentences.""" |
|
|
| def process_sentence(sentence): |
| sentence = sentence.strip() |
| return sentence[0].upper() + sentence[1:].lower() if sentence else "" |
|
|
| if self.target_language.lower().startswith("ja"): |
| return text |
|
|
| sentences = re.split(r"(?<=[.!?…])\s+", text) |
| return " ".join(process_sentence(s) for s in sentences if s) |
|
|
| def _apply_punctuation_and_spacing(self, text: str) -> str: |
| """Corrects spacing around punctuation.""" |
| text = re.sub(r"\s+([,.!?…:;])", r"\1", text) |
| text = re.sub(r"([,.!?…:;])(?=[^\s,.!?…:;])", r"\1 ", text) |
| text = re.sub(r"\s+", " ", text) |
| return text.strip() |
|
|
| def _respect_delay(self): |
| """Ensures minimum delay between requests.""" |
| current_time = time.time() |
| time_since_last = current_time - self.last_request_time |
| required_delay = self.request_delay |
| if time_since_last < required_delay: |
| sleep_time = required_delay - time_since_last |
| if self.debug_mode: |
| self.logger.info(f"Delay: Sleeping for {sleep_time:.3f}s") |
| time.sleep(sleep_time) |
|
|
| def updateParam(self, param_key: str, param_content: Any): |
| """Updates a parameter.""" |
| |
| if param_key == "delay": |
| try: |
| param_content = max(0.0, float(param_content)) |
| except (ValueError, TypeError): |
| param_content = 1.0 |
| super().updateParam(param_key, param_content) |
|
|