Burhan-Q

<core_identity> You are an assistant called Cluely, developed and created by Cluely, whose sole purpose is to analyze and solve problems asked by the user or shown on the screen. Your responses must be specific, accurate, and actionable. </core_identity>

<general_guidelines>

• NEVER use meta-phrases (e.g., "let me help you", "I can see that").
• NEVER summarize unless explicitly requested.
• NEVER provide unsolicited advice.
• NEVER refer to "screenshot" or "image" - refer to it as "the screen" if needed.
• ALWAYS be specific, detailed, and accurate.

Burhan-Q

from pathlib import Path

import torch
import torchvision
import yaml

from torchvision.transforms.v2 import Normalize
from torchvision.io import decode_image  # >= torchvision 0.20
from torchvision.io import read_image  # < torchvision 0.20
from ultralytics import YOLO

Burhan-Q

from typing import Any, Dict, Iterable


def dict_flatten(d: Dict[str, Any]) -> Dict[str, Any]:
    """Flattens nested dictionaries (but none in lists or tuples)."""
    res = {}
    for k, v in d.items():
        if isinstance(v, dict):
            res.update(dict_flatten(v))
        else:

Burhan-Q

<!-- Local run Ultralytics coverage report for PR https://github.com/ultralytics/ultralytics/pull/16442 -->
<?xml version="1.0" ?>
<coverage version="7.3.2" timestamp="1728481946686" lines-valid="17125" lines-covered="4468" line-rate="0.2609" branches-covered="0" branches-valid="0" branch-rate="0" complexity="0">
	<!-- Generated by coverage.py: https://coverage.readthedocs.io/en/7.3.2 -->
	<!-- Based on https://raw.githubusercontent.com/cobertura/web/master/htdocs/xml/coverage-04.dtd -->
	<sources>
		<source>ultralytics</source>
	</sources>
	<packages>
		<package name="." line-rate="0.5556" branch-rate="0" complexity="0">

Burhan-Q

'''
Author: Burhan Qaddoumi
Date: 2023-12-01
Requires: numpy, cv2

Please provide attribution.
'''
from pathlib import Path

import numpy as np

Burhan-Q

import torch
import cv2 as cv
import numpy as np
from torchvision.utils import draw_bounding_boxes

from ultralytics import YOLO
from ultralytics.utils.ops import Profile
from ultralytics.engine.results import Results

def fast_bbox(result:Results, l_width:int=3, np_out:bool=False):

Burhan-Q

from pathlib import Path

import torch
from torchvision.utils import draw_bounding_boxes

from ultralytics.utils import USER_CONFIG_DIR
from ultralytics.utils.plotting import colors
from ultralytics.engine.results import Results
from ultralytics.utils.checks import check_font, is_ascii