import datetime import logging import logging.handlers import os import sys from PIL import Image from io import BytesIO import base64 import numpy as np import requests from LLaVA.llava.constants import LOGDIR server_error_msg = "**NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.**" moderation_msg = "YOUR INPUT VIOLATES OUR CONTENT MODERATION GUIDELINES. PLEASE TRY AGAIN." handler = None def load_image_from_base64(image): return Image.open(BytesIO(base64.b64decode(image))) def build_logger(logger_name, logger_filename): global handler formatter = logging.Formatter( fmt="%(asctime)s | %(levelname)s | %(name)s | %(message)s", datefmt="%Y-%m-%d %H:%M:%S", ) # Set the format of root handlers if not logging.getLogger().handlers: logging.basicConfig(level=logging.INFO) logging.getLogger().handlers[0].setFormatter(formatter) # Redirect stdout and stderr to loggers stdout_logger = logging.getLogger("stdout") stdout_logger.setLevel(logging.INFO) sl = StreamToLogger(stdout_logger, logging.INFO) sys.stdout = sl stderr_logger = logging.getLogger("stderr") stderr_logger.setLevel(logging.ERROR) sl = StreamToLogger(stderr_logger, logging.ERROR) sys.stderr = sl # Get logger logger = logging.getLogger(logger_name) logger.setLevel(logging.INFO) # Add a file handler for all loggers if handler is None: os.makedirs(LOGDIR, exist_ok=True) filename = os.path.join(LOGDIR, logger_filename) handler = logging.handlers.TimedRotatingFileHandler( filename, when='D', utc=True) handler.setFormatter(formatter) for name, item in logging.root.manager.loggerDict.items(): if isinstance(item, logging.Logger): item.addHandler(handler) return logger class StreamToLogger(object): """ Fake file-like stream object that redirects writes to a logger instance. """ def __init__(self, logger, log_level=logging.INFO): self.terminal = sys.stdout self.logger = logger self.log_level = log_level self.linebuf = '' def __getattr__(self, attr): return getattr(self.terminal, attr) def write(self, buf): temp_linebuf = self.linebuf + buf self.linebuf = '' for line in temp_linebuf.splitlines(True): # From the io.TextIOWrapper docs: # On output, if newline is None, any '\n' characters written # are translated to the system default line separator. # By default sys.stdout.write() expects '\n' newlines and then # translates them so this is still cross platform. if line[-1] == '\n': self.logger.log(self.log_level, line.rstrip()) else: self.linebuf += line def flush(self): if self.linebuf != '': self.logger.log(self.log_level, self.linebuf.rstrip()) self.linebuf = '' def disable_torch_init(): """ Disable the redundant torch default initialization to accelerate model creation. """ import torch setattr(torch.nn.Linear, "reset_parameters", lambda self: None) setattr(torch.nn.LayerNorm, "reset_parameters", lambda self: None) def violates_moderation(text): """ Check whether the text violates OpenAI moderation API. """ url = "https://api.openai.com/v1/moderations" headers = {"Content-Type": "application/json", "Authorization": "Bearer " + os.environ["OPENAI_API_KEY"]} text = text.replace("\n", "") data = "{" + '"input": ' + f'"{text}"' + "}" data = data.encode("utf-8") try: ret = requests.post(url, headers=headers, data=data, timeout=5) flagged = ret.json()["results"][0]["flagged"] except requests.exceptions.RequestException as e: flagged = False except KeyError as e: flagged = False return flagged def pretty_print_semaphore(semaphore): if semaphore is None: return "None" return f"Semaphore(value={semaphore._value}, locked={semaphore.locked()})" def get_patch(bbox, image_width, image_height, patch_size=224, patch_scale=None): object_width = int(np.ceil(bbox[2])) object_height = int(np.ceil(bbox[3])) object_center_x = int(bbox[0] + bbox[2]/2) object_center_y = int(bbox[1] + bbox[3]/2) if patch_scale is None: patch_width = max(object_width, patch_size) patch_height = max(object_height, patch_size) else: patch_width = int(object_width*patch_scale) patch_height = int(object_height*patch_scale) left = max(0, object_center_x-patch_width//2) right = min(left+patch_width, image_width) top = max(0, object_center_y-patch_height//2) bottom = min(top+patch_height, image_height) return [left, top, right, bottom]