Delete src
Browse files- src/__init__.py +0 -0
- src/app/__init__.py +0 -0
- src/app/predict_pose.py +0 -68
- src/exception.py +0 -50
- src/logger.py +0 -21
src/__init__.py
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src/app/__init__.py
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src/app/predict_pose.py
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import sys
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import PIL.Image as Image
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from ultralytics import YOLO
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import gradio as gr
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import spaces
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# Local imports
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from src.logger import logging
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from src.exception import CustomExceptionHandling
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@spaces.GPU
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def predict_pose(
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img: str,
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conf_threshold: float,
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iou_threshold: float,
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max_detections: int,
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model_name: str,
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) -> Image.Image:
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"""
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Predicts objects in an image using a YOLOv8 model with adjustable confidence and IOU thresholds.
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Args:
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- img (str or numpy.ndarray): The input image or path to the image file.
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- conf_threshold (float): The confidence threshold for object detection.
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- iou_threshold (float): The Intersection Over Union (IOU) threshold for non-max suppression.
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- max_detections (int): The maximum number of detections allowed.
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- model_name (str): The name or path of the YOLOv8 model to be used for prediction.
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Returns:
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PIL.Image.Image: The image with predicted objects plotted on it.
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"""
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try:
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# Check if image is None
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if img is None:
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gr.Warning("Please provide an image.")
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# Load the YOLO model
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model = YOLO(model_name)
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# Predict objects in the image
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results = model.predict(
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source=img,
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conf=conf_threshold,
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iou=iou_threshold,
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max_det=max_detections,
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show_labels=True,
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show_conf=True,
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imgsz=640,
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half=True,
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device="cuda:0",
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)
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# Plot the predicted objects on the image
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for r in results:
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im_array = r.plot()
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im = Image.fromarray(im_array[..., ::-1])
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# Log the successful prediction
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logging.info("Pose estimated successfully.")
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# Return the image
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return im
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# Handle exceptions that may occur during the process
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except Exception as e:
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# Custom exception handling
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raise CustomExceptionHandling(e, sys) from e
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src/exception.py
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"""
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This module defines a custom exception handling class and a function to get error message with details of the error.
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"""
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# Standard Library
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import sys
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# Local imports
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from src.logger import logging
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# Function Definition to get error message with details of the error (file name and line number) when an error occurs in the program
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def get_error_message(error, error_detail: sys):
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"""
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Get error message with details of the error.
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Args:
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- error (Exception): The error that occurred.
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- error_detail (sys): The details of the error.
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Returns:
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str: A string containing the error message along with the file name and line number where the error occurred.
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"""
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_, _, exc_tb = error_detail.exc_info()
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# Get error details
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file_name = exc_tb.tb_frame.f_code.co_filename
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return "Error occured in python script name [{0}] line number [{1}] error message[{2}]".format(
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file_name, exc_tb.tb_lineno, str(error)
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)
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# Custom Exception Handling Class Definition
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class CustomExceptionHandling(Exception):
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"""
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Custom Exception Handling:
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This class defines a custom exception that can be raised when an error occurs in the program.
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It takes an error message and an error detail as input and returns a formatted error message when the exception is raised.
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"""
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# Constructor
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def __init__(self, error_message, error_detail: sys):
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"""Initialize the exception"""
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super().__init__(error_message)
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self.error_message = get_error_message(error_message, error_detail=error_detail)
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def __str__(self):
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"""String representation of the exception"""
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return self.error_message
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src/logger.py
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# Importing the required modules
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import os
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import logging
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from datetime import datetime
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# Creating a log file with the current date and time as the name of the file
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LOG_FILE = f"{datetime.now().strftime('%m_%d_%Y_%H_%M_%S')}.log"
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# Creating a logs folder if it does not exist
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logs_path = os.path.join(os.getcwd(), "logs", LOG_FILE)
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os.makedirs(logs_path, exist_ok=True)
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# Setting the log file path and the log level
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LOG_FILE_PATH = os.path.join(logs_path, LOG_FILE)
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# Configuring the logger
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logging.basicConfig(
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filename=LOG_FILE_PATH,
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format="[ %(asctime)s ] %(lineno)d %(name)s - %(levelname)s - %(message)s",
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level=logging.INFO,
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)
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