Bernat Puig Camps bepuca

## load_coco_dataset.py
# Copyright © 2022 Bernat Puig Camps
import json
from pathlib import Path
from typing import Tuple

import pandas as pd

DATA_PATH = Path("./coco_val2017")


## get_obj_det_predictions.py
# Copyright © 2022 Bernat Puig Camps
from pathlib import Path

import pandas as pd
from PIL import Image
import torch
import torchvision


def get_predictions(

## classify_errors.py
# Copyright © 2022 Bernat Puig Camps
from typing import Dict, Set, Tuple

import numpy as np
import pandas as pd
import torch
import torchvision

TARGETS_DF_COLUMNS = [
    "target_id",

## my_map.py
# Copyright © 2022 Bernat Puig Camps
import torch
from torchmetrics.detection.mean_ap import MeanAveragePrecision


class MyMeanAveragePrecision:
    """Wrapper for the torchmetrics MeanAveragePrecision exposing API we need"""

    def __init__(self, foreground_threshold):
        self.device = (

## error_impact.py
# Copyright © 2022 Bernat Puig Camps
from typing import Callable, Dict, Tuple

import pandas as pd

from classify_errors import PREDS_DF_COLUMNS, TARGETS_DF_COLUMNS, ErrorType


def calculate_error_impact(
    metric_name: str,

## test_obj_det_error.py
# Copyright © 2022 Bernat Puig Camps
import pandas as pd
import pytest

from classify_errors import (
    PREDS_DF_COLUMNS,
    TARGETS_DF_COLUMNS,
    ErrorType,
    classify_predictions_errors,
)

## object_detection_error_analysis_article.ipynb

      
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                bepuca
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              April 28, 2024 14:37
            
              
                object detection error analysis article - Interactive version of the article as a Jupyter notebook
              
          
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	# Copyright © 2022 Bernat Puig Camps
	import json
	from pathlib import Path
	from typing import Tuple

	import pandas as pd

	DATA_PATH = Path("./coco_val2017")
	# Copyright © 2022 Bernat Puig Camps
	from typing import Dict, Set, Tuple

	import numpy as np
	import pandas as pd
	import torch
	import torchvision

	TARGETS_DF_COLUMNS = [
	"target_id",
	# Copyright © 2022 Bernat Puig Camps
	import torch
	from torchmetrics.detection.mean_ap import MeanAveragePrecision


	class MyMeanAveragePrecision:
	"""Wrapper for the torchmetrics MeanAveragePrecision exposing API we need"""

	def __init__(self, foreground_threshold):
	self.device = (
	# Copyright © 2022 Bernat Puig Camps
	from typing import Callable, Dict, Tuple

	import pandas as pd

	from classify_errors import PREDS_DF_COLUMNS, TARGETS_DF_COLUMNS, ErrorType


	def calculate_error_impact(
	metric_name: str,
	# Copyright © 2022 Bernat Puig Camps
	import pandas as pd
	import pytest

	from classify_errors import (
	PREDS_DF_COLUMNS,
	TARGETS_DF_COLUMNS,
	ErrorType,
	classify_predictions_errors,
	)