{
"cells": [
{
"cell_type": "markdown",
"id": "71b1eb19-3148-46ca-8a9a-fdf18bd2b18d",
"metadata": {},
"source": [
"# Demonstrating Radial Distortion Perturbations\n",
"\n",
"## Introduction\n",
"This notebook is part of the NRTK demonstration suite, demonstrating how perturbations can be applied and their impact measured via MAITE evaluation workflows.\n",
"\n",
"## Layout\n",
"This notebook demonstrates how a particular augmentation (in this case, Radial Distortion of the Image), can affect an object detection model, and how that impact can be measured. The overall structure is:\n",
"\n",
"- **Traditional vs. Relative mAP:**\n",
" - An overview of the nuances of what we'll be evaluating.\n",
"- **Setup:**\n",
" - Notebook initialization, loading the supporting python code. Depending on if this is the first time you've run this notebook, this may take some time.\n",
" - Loading the source image, which will be used throughout the notebook.\n",
"- **Image Perturbation Examples:**\n",
" - The NRTK perturbation is demonstrated on the source image.\n",
"- **Baseline Detections:**\n",
" - The object detection model is loaded and run on the unperturbed image. These will serve as \\\"ground truth\\\" for comparisons against the perturbed images.\n",
" \n",
"At this point, we have the fundamental elements of our evaluation: the model, our reference image, and a mechanism for creating the perturbed test images. Next we adapt these elements to be used with the MAITE evaluation workflow:\n",
"\n",
"- **Wrapping the Detection Model**\n",
"- **Wrapping the Reference Image as a Dataset**\n",
"- **Wrapping the Perturbation as Augmentation Objects**\n",
"- **Wrapping the Metrics**\n",
"\n",
"After the evaluation elements have been wrapped, we can run the evaluation:\n",
"\n",
"- **Preparing the Augmentations:**\n",
" - We specify the range of perturbation values to evaluate and optionally specify which ones we'd like to visualize.\n",
"- **Evaluation of Augmented Data:**\n",
" - Each augmentation is run through MAITE's evaluation workflow, computing the mean average precision metric relative to the unperturbed detections.\n",
"- **Evaluation Analysis:**\n",
" - We plot and discuss the mAP@50 metric from each of the perturbed images, as well as per-class and per-area results.\n",
"\n",
"To run this notebook in Colab, use the link below:\n",
"\n",
"[](https://colab.research.google.com/github/Kitware/nrtk/blob/main/docs/examples/maite/nrtk_radial_distortion_perturber_demo.ipynb)"
]
},
{
"cell_type": "markdown",
"id": "4b2e1964-46e2-4497-88ff-274eaca17960",
"metadata": {},
"source": [
"## Evaluation Guidance: Traditional vs. Relative mAP\n",
"\n",
"This notebook will be evaluating the perturbed images using mean average precision (mAP) **relative** to detections from the unperturbed image. Traditional mAP scores the computed detections to ground-truth annotations vetted by an analyst; the mAP metric indicates how well the detector does compared to that analyst and thus measures the detector's \"absolute\" performance (\"absolute\" in the sense that the assumption is no detector can do better than the analyst.)\n",
"\n",
"In contrast, in this notebook, we're not concerned with the **absolute** ability of the detector to find objects of interest. Rather, we're interested in how the **perturbations** affect the detector *relative to the unperturbed image*. It's expected that the detector won't find every target in the unperturbed image; instead, we're measuring the **change in the detections** (or classifications) caused by the perturbations.\n",
"\n",
"To support relative mAP, we'll be computing detections on the unperturbed image and using those as our \"ground truth\" dataset, and using the MAITE dataset class slightly differently than usual. For example, there's no on-disk json file of reference annotations with an associated data loader; instead, we'll be taking the computed detections and manually copying them over into the dataset."
]
},
{
"cell_type": "markdown",
"id": "f9268412-0d13-4fed-ae78-f6ee02c94c9c",
"metadata": {},
"source": [
"## Setup: Notebook Initialization\n",
"The next few cells import the python packages used in the rest of the notebook.\n",
"\n",
"**Note:** We are suppressing warnings within this notebook to reduce visual clutter for demonstration purposes. If any issues arise while executing this notebook, we recommend that the first cell is **not** executed so that any related warnings are shown."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "796743f8-2f1e-42aa-ad6b-f71e721602f8",
"metadata": {},
"outputs": [],
"source": [
"from __future__ import annotations\n",
"\n",
"# warning suppression\n",
"import warnings\n",
"\n",
"warnings.filterwarnings(\"ignore\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "2561179f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Beginning package installation...\n",
"Installing required packages...\n",
"Doing a fresh install of opencv-python-headless...\n",
"\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
"ultralytics 8.3.85 requires opencv-python>=4.6.0, which is not installed.\n",
"maite 0.7.1 requires numpy<2,>=1.24.2, but you have numpy 2.2.6 which is incompatible.\n",
"nrtk 0.23.0 requires numpy<2.0,>=1.22; python_version < \"3.12\", but you have numpy 2.2.6 which is incompatible.\n",
"numba 0.60.0 requires numpy<2.1,>=1.22, but you have numpy 2.2.6 which is incompatible.\n",
"pybsm 0.10.2 requires numpy<2.0,>=1.22; python_version < \"3.12\", but you have numpy 2.2.6 which is incompatible.\n",
"smqtk-classifier 0.19.0 requires numpy<2.0.0,>=1.19.5, but you have numpy 2.2.6 which is incompatible.\n",
"ultralytics 8.3.85 requires numpy<=2.1.1,>=1.23.0, but you have numpy 2.2.6 which is incompatible.\n",
"xaitk-jatic 0.5.0 requires numpy<2.0,>=1.22; python_version < \"3.12\", but you have numpy 2.2.6 which is incompatible.\n",
"xaitk-saliency 0.12.0 requires numpy<2.0,>=1.25; python_version >= \"3.9\" and python_version < \"3.12\", but you have numpy 2.2.6 which is incompatible.\u001b[0m\u001b[31m\n",
"\u001b[0m"
]
}
],
"source": [
"import sys # noqa: F401\n",
"\n",
"print(\"Beginning package installation...\")\n",
"!{sys.executable} -m pip install -qU pip\n",
"\n",
"print(\"Installing required packages...\")\n",
"!{sys.executable} -m pip install -q \"nrtk[maite]\" --no-cache-dir\n",
"!{sys.executable} -m pip install -q \"matplotlib\" --no-cache-dir\n",
"!{sys.executable} -m pip install -q \"torchvision\" --no-cache-dir\n",
"!{sys.executable} -m pip install -q \"torchmetrics\" --no-cache-dir\n",
"!{sys.executable} -m pip install -q \"ultralytics\" --no-cache-dir\n",
"\n",
"# OpenCV must be uninstalled and reinstalled last due to other packages installing OpenCV\n",
"print(\"Doing a fresh install of opencv-python-headless...\")\n",
"!{sys.executable} -m pip uninstall -qy \"opencv-python\" \"opencv-python-headless\"\n",
"!{sys.executable} -m pip install -q \"opencv-python-headless\" --no-cache-dir"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "c18e6bd1-1c56-447a-b1e4-16df26269ed8",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import urllib.request\n",
"from collections.abc import Sequence\n",
"from typing import Any\n",
"\n",
"import numpy as np\n",
"\n",
"# some initial imports\n",
"%matplotlib inline\n",
"%config InlineBackend.figure_format = \"jpeg\" # Use JPEG format for inline visualizations\n",
"\n",
"from matplotlib import pyplot as plt\n",
"from PIL import Image\n",
"\n",
"from nrtk.impls.perturb_image.generic.radial_distortion_perturber import RadialDistortionPerturber"
]
},
{
"cell_type": "markdown",
"id": "242e9bfa-fcea-4a1d-a8e0-9455b28777a2",
"metadata": {},
"source": [
"## Setup: Source Image\n",
"\n",
"In the next cell, we'll download and display a source image from the __[VisDrone](https://github.com/VisDrone/VisDrone-Dataset)__ dataset. The image will be cached in a local `data` subdirectory.\n",
"\n",
"### A Note on Image Storage\n",
"\n",
"Typically in ML workflows, batches of images are processed as tensors of the color channels. Both our perturber (NRTK) and object detector (YOLO) accept numpy `ndarray` objects, and we will use [matplotlib.imshow](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html) to view them. The complication is that although YOLO inferences on `ndarray`, [it expects the color channels to be in BGR](https://docs.ultralytics.com/modes/predict/) order. If we naively view the same data YOLO inferences on, the colors will be wrong; if we naively inference on what we view, the detections will be wrong. (Our NRTK perturbation is agnostic to the channel order.)\n",
"\n",
"In this notebook, we'll convert the channel order to BGR when we load, and convert back whenever we explicitly call `imshow`.\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "57facb8b-4cb6-476b-a321-f48d70e773ba",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(540, 960, 3)\n"
]
},
{
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data_dir = \"./data\"\n",
"os.makedirs(data_dir, exist_ok=True)\n",
"img_path = os.path.join(data_dir, \"visdrone_img.jpg\")\n",
"if not os.path.isfile(img_path):\n",
" url = \"https://data.kitware.com/api/v1/item/623880f14acac99f429fe3ca/download\"\n",
" _ = urllib.request.urlretrieve(url, img_path) # noqa: S310\n",
"\n",
"img_pil = Image.open(img_path)\n",
"img_nd_bgr = np.asarray(img_pil)[\n",
" :,\n",
" :,\n",
" ::-1,\n",
"] # tip o' the hat to https://stackoverflow.com/questions/4661557/pil-rotate-image-colors-bgr-rgb\n",
"plt.figure()\n",
"plt.axis(\"off\")\n",
"print(img_nd_bgr.shape)\n",
"_ = plt.imshow(img_nd_bgr[:, :, ::-1]) # explicitly changing BGR to RGB for imshow"
]
},
{
"cell_type": "markdown",
"id": "efe2e2a3-a3a2-4101-9872-bae618effab0",
"metadata": {},
"source": [
"## NRTK Radial Distortion Perturbation: Examples and Guidance\n",
"\n",
"The [Radial Distortion perturbation]() simulates lens distortion effects, such as\n",
"barrel or pincushion distortion, and is useful for augmenting datasets to improve\n",
"robustness to camera nonlinearities.\n",
"\n",
"The distortion uses the following equations:\n",
"\n",
"- `x1 = x0 * (1 + k1*r^2 + k2*r^4 + k3*r^6)`\n",
"- `y1 = y0 * (1 + k1*r^2 + k2*r^4 + k3*r^6)`\n",
" \n",
"Where:\n",
"- `x0` and `y0` are normalized coordinates between `[-1, 1]`.\n",
"- `r` is the distance from the image center.\n",
"- `k1`, `k2`, and `k3` are distortion coefficients.\n",
"\n",
"\n",
"The `RadialDistortionPerturber` takes the following inputs in order to perform the distortion:\n",
"- `color_fill`: A list of 3 values between `0` and `255` representing the background color to fill portions of the output image which do not have a corresponding value in the original image.\n",
"- `k`: A list of 3 values representing `k1`, `k2`, and `k3` in the above equations. These coefficients are typically very small negative or positive values. Negative coefficients represent a pinhole distortion while positive coefficients represent a barrel/fisheye distortion.\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "5a370d2a-2489-4c48-b29a-ea8ad3ef98fa",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"_, ax = plt.subplots(2, 4, figsize=(10, 4))\n",
"for idx, k in enumerate([-0.2, -0.1, 0, 0.02, 0.04, 0.06, 0.08, 0.1]):\n",
" (row, col) = (int(idx / 4), idx % 4)\n",
" bp = RadialDistortionPerturber(color_fill=(0, 0, 0), k=[k, 0, 0])\n",
" ax[row, col].set_title(f\"k1: {k}\")\n",
" ax[row, col].imshow(bp(img_nd_bgr)[0][:, :, ::-1])\n",
" _ = ax[row, col].axis(\"off\")\n",
"plt.tight_layout()"
]
},
{
"cell_type": "markdown",
"id": "30eb653b-6be9-4d58-8d69-db4b64c3d81c",
"metadata": {},
"source": [
"## Baseline Detections\n",
"\n",
"In the next cell, we'll download a [YOLOv11](https://docs.ultralytics.com/models/yolo11/) model, compute object detections on the source image, and display the results. As discussed above, these detections will serve as the \"ground truth\" for our relative mAP evaluation later.\n",
"\n",
"*Note that here, we're using YOLO's built-in visualization tool, which automatically adjusts for BGR / RGB order.*"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "55600de0-089f-4dd6-ac4d-7896b8df5494",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Ultralytics 8.3.85 🚀 Python-3.10.12 torch-2.7.1+cu126 CUDA:0 (NVIDIA RTX A2000 Laptop GPU, 3782MiB)\n",
"Setup complete ✅ (16 CPUs, 62.5 GB RAM, 398.1/914.7 GB disk)\n",
"Downloading model...\n",
"Computing baseline...\n",
"\n",
"0: 384x640 5 persons, 15 cars, 1 motorcycle, 2 trucks, 44.8ms\n",
"Speed: 3.5ms preprocess, 44.8ms inference, 82.3ms postprocess per image at shape (1, 3, 384, 640)\n"
]
}
],
"source": [
"# Import YOLO support\n",
"import ultralytics\n",
"\n",
"ultralytics.checks()\n",
"print(\"Downloading model...\")\n",
"model = ultralytics.YOLO(\"yolo11n.pt\")\n",
"print(\"Computing baseline...\")\n",
"baseline = model(img_nd_bgr)"
]
},
{
"cell_type": "markdown",
"id": "39050929-bf48-44b1-9247-5cac7f44cd8c",
"metadata": {},
"source": [
"## MAITE Evaluation Workflow Preparation\n",
"\n",
"We'll use the [MAITE Evaluation workflow](https://jatic.pages.jatic.net/cdao/maite/generated/maite.tasks.evaluate.html) to evaluate the performance of the perturbed data against our baseline detections. We'll need to \"wrap\" our model, data, and perturbations into callable objects to pass to the `maite.tasks.evaluate` function:\n",
"\n",
"- We'll wrap the **model** to make predictions on input data when called.\n",
"\n",
"- The wrapped **dataset** will return our test image when called. Note that this will be the original, unperturbed image; we'll apply our perturbations via...\n",
"\n",
"- ...the **augmentation** object, which applies the perturbation to the image inside the evaluation.\n",
"\n",
"- Finally, the **metric** object will define our precise scoring methodology.\n",
"\n",
"The evaluation workflow in this notebook is slightly unusual. Typical ML workflows apply many different augmentations / perturbations to much larger datasets, and only call `evaluate` once to get a statistical view of performance. But since the goal of this notebook is to drill down into how perturbation affects performance, we've essentially flipped the process, calling `evaluate` (and thus our wrapped objects) many times, once per loop on our single image perturbed to a known degree, and then observing how the metrics respond."
]
},
{
"cell_type": "markdown",
"id": "da908c7f-b499-4361-8e2b-cf7647b45de6",
"metadata": {},
"source": [
"### Some Helper Classes\n",
"\n",
"The following cell adds two classes to allow us to use YOLO detections with the MAITE evaluation workflow:\n",
"\n",
"1. The `YOLODetectionTarget` helper class that stores the bounding boxes, label indices, and confidence scores for a single image's detections.\n",
"\n",
"2. The `MaiteYOLODetection` adapter class that conforms to the MAITE [Object Detection Dataset](https://jatic.pages.jatic.net/cdao/maite/generated/maite.protocols.object_detection.Dataset.html) protocol by providing the `__len__` and `__getitem__` methods. The returned item is a tuple of (image, `YOLODetectionTarget`, metadata-dictionary)."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "346f4207",
"metadata": {},
"outputs": [],
"source": [
"from dataclasses import dataclass\n",
"\n",
"import torch\n",
"from maite.protocols.object_detection import DatumMetadataType\n",
"\n",
"from nrtk.interop.maite.interop.object_detection.dataset import JATICObjectDetectionDataset\n",
"\n",
"##\n",
"## Helper class for containing the boxes, label indices, and confidence scores.\n",
"##\n",
"\n",
"\n",
"@dataclass\n",
"class DetectionDatumMetadata(DatumMetadataType):\n",
" \"\"\"Dataclass for detection datum-level metadata.\"\"\"\n",
"\n",
" id: int | str\n",
" k: tuple[float, float, float]\n",
"\n",
"\n",
"@dataclass\n",
"class YOLODetectionTarget:\n",
" \"\"\"A helper class to represent object detection results in the format expected by YOLO-based models.\n",
"\n",
" Attributes:\n",
" boxes (torch.Tensor): A tensor containing the bounding boxes for detected objects in\n",
" [x_min, y_min, x_max, y_max] format.\n",
" labels (torch.Tensor): A tensor containing the class labels for the detected objects.\n",
" These may be floats for compatibility with specific datasets or tools.\n",
" scores (torch.Tensor): A tensor containing the confidence scores for the detected objects.\n",
" \"\"\"\n",
"\n",
" boxes: torch.Tensor\n",
" labels: torch.Tensor\n",
" scores: torch.Tensor\n",
"\n",
"\n",
"##\n",
"## Prepare results for ingestion into maite dataset by puttin them into detection object\n",
"## Images must be channel first (c, h, w) in maite dataset objects\n",
"##\n",
"imgs = [np.transpose(img_nd_bgr, (2, 0, 1))]\n",
"dets = []\n",
"metadata: list[DatumMetadataType] = [{\"id\": 0}]\n",
"for _detection in baseline:\n",
" boxes = baseline[0].boxes.xyxy.cpu()\n",
" labels = baseline[0].boxes.cls.cpu() # note, these are floats, not ints\n",
" scores = baseline[0].boxes.conf.cpu()\n",
"\n",
" dets.append(YOLODetectionTarget(boxes, labels, scores))"
]
},
{
"cell_type": "markdown",
"id": "45cd8fb3-2ea6-492c-ab84-f3432b9d3440",
"metadata": {},
"source": [
"### (1) Wrapping the Detection Model\n",
"\n",
"The first object we'll wrap will be the detection model. The cell below defines a class adapting YOLO for the [MAITE Object Detection Model](https://jatic.pages.jatic.net/cdao/maite/generated/maite.protocols.object_detection.Model.html) protocol. The `__call__` method runs the model on images in the batch and is called by the MAITE evaluation workflow later in the notebook."
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "e1131aa7-3716-479f-838b-0464b74106e9",
"metadata": {},
"outputs": [],
"source": [
"import maite.protocols.object_detection as od\n",
"import ultralytics.models\n",
"from maite.protocols import ArrayLike, ModelMetadata\n",
"\n",
"\n",
"class MaiteYOLODetector:\n",
" \"\"\"A wrapper class for a YOLO model to simplify its usage with input batches and object detection targets.\n",
"\n",
" This class takes a YOLO model instance, processes input image batches, and converts predictions into\n",
" `YOLODetectionTarget` instances.\n",
"\n",
" Attributes:\n",
" _model (ultralytics.models.yolo.model.YOLO): The YOLO model instance used for predictions.\n",
"\n",
" Methods:\n",
" __call__(batch):\n",
" Processes a batch of images through the YOLO model and returns the predictions as\n",
" `YOLODetectionTarget` instances.\n",
" \"\"\"\n",
"\n",
" def __init__(self, model: ultralytics.models.yolo.model.YOLO) -> None:\n",
" \"\"\"Initializes the MaiteYOLODetector with a YOLO model instance.\n",
"\n",
" Args:\n",
" model (ultralytics.models.yolo.model.YOLO): The YOLO model to use for predictions.\n",
" \"\"\"\n",
" self._model = model\n",
" # Dummy model metadata type to pass type checking\n",
" self.metadata = ModelMetadata(id=\"0\")\n",
"\n",
" def __call__(self, batch: Sequence[ArrayLike]) -> Sequence[YOLODetectionTarget]:\n",
" \"\"\"Processes a batch of images using the YOLO model and converts the predictions to `YOLODetectionTarget`s.\n",
"\n",
" Args:\n",
" batch (Sequence[ArrayLike]): A batch of images in (c, h, w) format (channel-first).\n",
"\n",
" Returns:\n",
" Sequence[YOLODetectionTarget]: A list of YOLODetectionTarget instances containing the predictions for each\n",
" image in the batch.\n",
" \"\"\"\n",
" # Convert images to channel-last format (h, w, c) for YOLO model\n",
" batch_transposed = [np.transpose(batch[i], (1, 2, 0)) for i in range(len(batch))]\n",
"\n",
" yolo_predictions = self._model(batch_transposed, verbose=False)\n",
" return [\n",
" YOLODetectionTarget(\n",
" p.boxes.xyxy.cpu(), # Bounding boxes in (x_min, y_min, x_max, y_max) format\n",
" p.boxes.cls.cpu(), # Class indices for the detected objects\n",
" p.boxes.conf.cpu(), # Confidence scores for the detections\n",
" )\n",
" for p in yolo_predictions\n",
" ]\n",
"\n",
"\n",
"# create the wrapped model object\n",
"yolo_model: od.Model = MaiteYOLODetector(model)"
]
},
{
"cell_type": "markdown",
"id": "3cef0788-137f-41c1-a9e4-80e7d08b47d1",
"metadata": {},
"source": [
"### (2) Wrapping the Dataset\n",
"\n",
"MAITE pairs images and their reference detections (aka targets, ground truth) into **datasets**. Typical ML workflows have many images per dataset; when these do not all fit in memory simultaneously, a *dataloader* object is used which can page images and annotations in from disk. For this notebook, however, each invocation of `evaluate` will use the same single-image dataset (our reference image with its baseline detections.)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "1dcbb5d0-b899-4355-9922-9d52fb866b4b",
"metadata": {},
"outputs": [],
"source": [
"# our single image, its baseline detections, and an empty metadata dictionary\n",
"# switch image to channel first\n",
"single_image_dataset: od.Dataset = JATICObjectDetectionDataset(imgs, dets, metadata, dataset_id=\"visdrone_ex\")"
]
},
{
"cell_type": "markdown",
"id": "7963f7fa-052c-476d-944e-5bbdae3181b5",
"metadata": {},
"source": [
"### (3) Wrapping the Perturbations as Augmentations\n",
"\n",
"The `evaluate` function will perturb the image from the dataset using instances of the class defined below, one instance per perturbation value. Note that the object doesn't perform any augmentations until called by the `evaluate` workflow."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "aa7a398f",
"metadata": {},
"outputs": [],
"source": [
"from nrtk.interop.maite.interop.object_detection.augmentation import JATICDetectionAugmentation\n",
"\n",
"bp = RadialDistortionPerturber(k=[0, 0, 0])\n",
"identity_augmentation = JATICDetectionAugmentation(bp, augment_id=\"identity\")"
]
},
{
"cell_type": "markdown",
"id": "81020be7-76ba-43e3-b231-7d2bd7c30387",
"metadata": {},
"source": [
"### (4) Wrapping the Metrics\n",
"\n",
"We'll compare the detections in each perturbed image to the unperturbed detections using the Mean Average Precision (mAP) metric from the `torchmetrics` package. The following cell creates a mAP metrics object, wraps it in a MAITE [MAITE Object Detection Metric](https://jatic.pages.jatic.net/cdao/maite/generated/maite.protocols.object_detection.Metric.html) protocol-compatible class, and then creates an instance of this class, which will be called by `evaluate`.\n",
"\n",
"This code is copied directly from the [MAITE object detection tutorial](https://jatic.pages.jatic.net/cdao/maite/tutorials/torchvision_object_detection.html#metrics) (with the exception of setting `class_metrics=True`.)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "e33407c5-f1d7-4c7a-9a31-2d500f97edcc",
"metadata": {},
"outputs": [],
"source": [
"from maite.protocols import MetricMetadata\n",
"from torchmetrics import Metric as TorchMetric\n",
"from torchmetrics.detection.mean_ap import MeanAveragePrecision\n",
"\n",
"##\n",
"## Create an instance of the MAP metric object\n",
"##\n",
"\n",
"tm_metric = MeanAveragePrecision(\n",
" box_format=\"xyxy\",\n",
" iou_type=\"bbox\",\n",
" iou_thresholds=[0.5],\n",
" rec_thresholds=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0],\n",
" max_detection_thresholds=[1, 10, 100],\n",
" class_metrics=True,\n",
" extended_summary=False,\n",
" average=\"macro\",\n",
")\n",
"\n",
"##\n",
"## This wrapper associates the MAP metric object with methods called by the evaluate\n",
"## workflow to accumulate detection data and compute the metrics.\n",
"##\n",
"\n",
"\n",
"class WrappedTorchmetricsMetric:\n",
" \"\"\"A wrapper class for a Torchmetrics metric designed to simplify its usage for object detection tasks.\n",
"\n",
" This class facilitates the conversion of object detection targets and predictions into the format\n",
" expected by Torchmetrics metrics, allowing for easier integration with existing pipelines.\n",
"\n",
" Attributes:\n",
" _tm_metric (Callable): The Torchmetrics metric to be wrapped, which takes lists of dictionaries\n",
" containing torch.Tensor objects representing predictions and targets.\n",
"\n",
" Methods:\n",
" to_tensor_dict(target):\n",
" Converts an `ObjectDetectionTarget` into a dictionary format compatible with the Torchmetrics\n",
" metric's `update` method.\n",
"\n",
" update(preds, targets):\n",
" Updates the wrapped Torchmetrics metric with batches of predictions and targets in their native format.\n",
"\n",
" compute():\n",
" Computes the final metric values using the wrapped Torchmetrics metric.\n",
"\n",
" reset():\n",
" Resets the state of the wrapped Torchmetrics metric.\n",
" \"\"\"\n",
"\n",
" def __init__(\n",
" self,\n",
" tm_metric: TorchMetric,\n",
" ) -> None:\n",
" \"\"\"Initializes the WrappedTorchmetricsMetric with the given Torchmetrics metric.\n",
"\n",
" Args:\n",
" tm_metric (Callable): A Torchmetrics metric instance that expects predictions and targets as lists of\n",
" dictionaries containing torch.Tensor objects.\n",
" \"\"\"\n",
" self._tm_metric = tm_metric\n",
" # Dummy metric metadata type to pass type checking\n",
" self.metadata = MetricMetadata(id=\"0\")\n",
"\n",
" @staticmethod\n",
" def to_tensor_dict(target: od.ObjectDetectionTarget) -> dict[str, torch.Tensor]:\n",
" \"\"\"Converts an ObjectDetectionTarget into a dictionary format compatible with the Torch's `update` method.\n",
"\n",
" Args:\n",
" target (od.ObjectDetectionTarget): An object detection target instance containing boxes, labels, and scores.\n",
"\n",
" Returns:\n",
" dict[str, torch.Tensor]: A dictionary with keys `boxes`, `scores`, and `labels`, each mapping to a tensor.\n",
" \"\"\"\n",
" return {\n",
" \"boxes\": torch.as_tensor(target.boxes),\n",
" \"scores\": torch.as_tensor(target.scores),\n",
" \"labels\": torch.as_tensor(target.labels).type(torch.int64),\n",
" }\n",
"\n",
" def update(self, preds: Sequence[od.TargetType], targets: Sequence[od.TargetType]) -> None:\n",
" \"\"\"Updates the wrapped Torchmetrics metric with the given predictions and targets.\n",
"\n",
" Args:\n",
" preds (Sequence[od.TargetType]): A batch of predictions in the format expected by the Torchmetrics metric.\n",
" targets (Sequence[od.TargetType]): A batch of targets in the format expected by the Torchmetrics metric.\n",
" \"\"\"\n",
" preds_tm = [self.to_tensor_dict(pred) for pred in preds]\n",
" targets_tm = [self.to_tensor_dict(tgt) for tgt in targets]\n",
" self._tm_metric.update(preds_tm, targets_tm)\n",
"\n",
" def compute(self) -> dict[str, Any]:\n",
" \"\"\"Computes and returns the final metric values using the wrapped Torchmetrics metric.\n",
"\n",
" Returns:\n",
" dict[str, Any]: A dictionary containing the computed metric values.\n",
" \"\"\"\n",
" return self._tm_metric.compute()\n",
"\n",
" def reset(self) -> None:\n",
" \"\"\"Resets the state of the wrapped Torchmetrics metric, clearing any accumulated data.\"\"\"\n",
" self._tm_metric.reset()\n",
"\n",
"\n",
"##\n",
"## This is our instance variable that can compute the MAP metrics.\n",
"##\n",
"\n",
"mAP_metric: od.Metric = WrappedTorchmetricsMetric(tm_metric) # noqa: N816"
]
},
{
"cell_type": "markdown",
"id": "0102dfde-cb9b-46a7-8e4a-d12ccd948864",
"metadata": {},
"source": [
"## Running the Evaluation\n",
"\n",
"We now have all the wrappings required to evaluate our range of perturbations:\n",
"- The `yolo_model` object, wrapping the YOLO model\n",
"- The `single_image_dataset` object, providing our source image and its baseline detections\n",
"- The `augmentation` object, which when instantiated, applies a single perturbation value to its input\n",
"- The `mAP_metrics` object, defining the metrics to compute at each perturbation value"
]
},
{
"cell_type": "markdown",
"id": "38a7fef1-a3cc-4e63-8a2b-6133274e4b1c",
"metadata": {},
"source": [
"### Evaluation Sanity Check: Ground Truth Against Itself\n",
"\n",
"Here we quickly check the evaluation workflow by creating an *identity augmentation* (with a brightness perturbation factor of 1.0, leaving the image unchanged) and scoring it. The detections should also be unchanged from the baseline and thus give an mAP of 1.0."
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "a0af9f36-c69b-400f-82ec-f1fd7e9d98ea",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 26.19it/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Sanity check: overall mAP (should be 1.0): 1.0\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"from maite.tasks import evaluate\n",
"\n",
"# call the model for each image in the dataset (in this case, just the source image),\n",
"# scoring the resulting detections against those from the dataset\n",
"sanity_check_results, _, _ = evaluate(\n",
" model=yolo_model,\n",
" dataset=single_image_dataset,\n",
" augmentation=identity_augmentation,\n",
" metric=mAP_metric,\n",
")\n",
"\n",
"print(\"Sanity check: overall mAP (should be 1.0):\", sanity_check_results[\"map\"].item())"
]
},
{
"cell_type": "markdown",
"id": "2a1a72bb-dbf1-431e-892e-132771cd7b92",
"metadata": {},
"source": [
"### Preparing the Data\n",
"\n",
"Now we'll prepare the augmentation instances for the evaluation. In the cell below, you can set three parameters for sweeping the set of perturbation values:\n",
"- **sweep_low**: the minimum perturbation value (must be >= 0)\n",
"- **sweep_high**: the maximum perturbation value\n",
"- **sweep_count**: how many perturbations to generation\n",
"\n",
"You can also optionally select perturbations to visualize:\n",
"- **visualization_indices**: a list of perturbation indices *p*, 0 <= *p* < sweep_count. These instances will be rendered along with their corresponding detections."
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "48b5e334-d8eb-415c-b263-4c4bd3618b43",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Generated 30 perturbation datasets\n"
]
}
],
"source": [
"SWEEP_LOW = 0.001\n",
"SWEEP_HIGH = 0.2\n",
"SWEEP_COUNT = 30\n",
"VISUALIZATION_INDICES = [3, 9, 21]\n",
"\n",
"##\n",
"## end user-settable parameters\n",
"##\n",
"perturbation_values = np.linspace(SWEEP_LOW, SWEEP_HIGH, SWEEP_COUNT, endpoint=True)\n",
"augmentations = [\n",
" JATICDetectionAugmentation(RadialDistortionPerturber(k=[k1, 0, 0]), augment_id=str(idx))\n",
" for idx, k1 in enumerate(perturbation_values)\n",
"]\n",
"# create new pertruber for each dataset to preserve seed value\n",
"print(f\"Generated {len(augmentations)} perturbation datasets\")"
]
},
{
"cell_type": "markdown",
"id": "549d0d4d-eabd-4f54-a487-7cfbc99916c9",
"metadata": {},
"source": [
"### Calling Evaluate on the Augmented Data\n",
"\n",
"We loop over all the augmentations, calling `evaluate` on each one and building up a list of resulting metrics for analysis.\n",
"\n",
"Any augmentation indices specified above will be rendered in this step."
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "a4951dfc-c2cc-434a-8fd2-1786ba3acf96",
"metadata": {},
"outputs": [
{
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]
},
{
"name": "stdout",
"output_type": "stream",
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"Perturbation #3: k1 0.021586206896551725\n"
]
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{
"name": "stdout",
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"Perturbation #9: k1 0.06275862068965517\n"
]
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]
},
{
"name": "stdout",
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"Perturbation #21: k1 0.14510344827586208\n"
]
},
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]
},
{
"data": {
"image/jpeg": 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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"perturbed_metrics = list()\n",
"_, ax = plt.subplots(len(VISUALIZATION_INDICES), figsize=(30, 12))\n",
"for idx, a in enumerate(augmentations): # reset the metric object for each dataset\n",
" mAP_metric.reset()\n",
" k1: float = a.augment.get_config()[\"k\"][0]\n",
" perturber = RadialDistortionPerturber(k=[k1, 0, 0])\n",
" augmentation = JATICDetectionAugmentation(perturber, augment_id=str(idx))\n",
" result, _, _ = evaluate(\n",
" model=yolo_model,\n",
" dataset=single_image_dataset,\n",
" augmentation=augmentation,\n",
" metric=mAP_metric,\n",
" )\n",
" perturbed_metrics.append(result)\n",
"\n",
" if idx in VISUALIZATION_INDICES:\n",
" # quickest way is to re-evaluate\n",
" print(f\"Perturbation #{idx}: k1 {k1}\")\n",
" datum = single_image_dataset[0]\n",
" batch = ([datum[0]], [datum[1]], [datum[2]])\n",
" # Extract the image from the augmentation and switch it to channel last\n",
" aug = np.transpose(augmentation(batch)[0][0], (1, 2, 0))\n",
" # Plot image\n",
" ax_idx = VISUALIZATION_INDICES.index(idx)\n",
" ax[ax_idx].imshow(model(aug)[0].plot())\n",
" ax[ax_idx].set_title(f\"k1: {k1}\")\n",
" _ = ax[ax_idx].axis(\"off\")\n",
"plt.tight_layout()"
]
},
{
"cell_type": "markdown",
"id": "d0303b6a-f587-43c8-ae9f-0057a7884241",
"metadata": {},
"source": [
"## Evaluation Analysis\n",
"\n",
"Now we can plot how the metrics (for example, mAP @ IoU=50) vary with perturbation level, keeping in mind this is a **relative** mAP against the detections in the unperturbed image.\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "09b6804b-c98c-46fb-af98-ab5598892ba7",
"metadata": {},
"outputs": [
{
"data": {
"image/jpeg": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"map50_list = [m[\"map_50\"].item() for m in perturbed_metrics]\n",
"plt.title(\"relative mAP@50\")\n",
"plt.xlabel(\"Radial Distortion Coefficient (k)\")\n",
"plt.ylabel(\"relative mAP @ 50% IoU\")\n",
"_ = plt.plot(perturbation_values, map50_list)"
]
},
{
"cell_type": "markdown",
"id": "3a8720fd-32dc-493d-ab5c-81c313615504",
"metadata": {},
"source": [
"### Evaluation Interpretation\n",
"\n",
"The metric shown, mAP@50, is the average precision of detections across all classes when the bounding box IoU is at least 0.5 (for more details, [see here](https://lightning.ai/docs/torchmetrics/stable/detection/mean_average_precision.html).) As the value of the distortion coefficient increases, the relative mAP@50 decreases almost linearly. However, worth noting that the trend isn't strictly downwards, and occasionally an increase in the distortion coefficient results in a small improvement to the accuracy of detection."
]
},
{
"cell_type": "markdown",
"id": "3f0f9b97-ce54-4d21-be91-160f4a5d3054",
"metadata": {},
"source": [
"### Additional Plots\n",
"\n",
"For further insight, we can plot the mAP per class:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "65d28ff5-838e-467a-a703-81432a408b35",
"metadata": {},
"outputs": [
{
"data": {
"image/jpeg": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#\n",
"# Each instance of the metrics object has, potentially, a different set of observed classes.\n",
"# Loop through them to accumulate a unified set of classes to ensure consistent plotting across\n",
"# all thresholds.\n",
"#\n",
"\n",
"unified_classes = set()\n",
"for m in perturbed_metrics:\n",
" for class_idx in m[\"classes\"].tolist():\n",
" unified_classes.add(class_idx)\n",
"\n",
"#\n",
"# dictionary of class_idx -> list of per-class mAP, or 0 if not present at that threshold\n",
"#\n",
"\n",
"class_mAP = {class_idx: list() for class_idx in unified_classes} # noqa: N816\n",
"\n",
"#\n",
"# populate the lists across the perturbation values\n",
"#\n",
"\n",
"for m in perturbed_metrics:\n",
" this_perturbation_classes = m[\"classes\"].tolist()\n",
" for class_idx in unified_classes:\n",
" if class_idx in this_perturbation_classes:\n",
" # the index of the class in this individual metric instance\n",
" this_class_idx = this_perturbation_classes.index(class_idx)\n",
" class_mAP[class_idx].append(m[\"map_per_class\"][this_class_idx].item())\n",
" else:\n",
" class_mAP[class_idx].append(0)\n",
"\n",
"#\n",
"# plot\n",
"#\n",
"\n",
"plt.title(\"Relative mAP per class\")\n",
"plt.xlabel(\"Radial Distortion Coefficient (k)\")\n",
"plt.ylabel(\"relative mAP @ 50% IoU\")\n",
"for class_idx, class_mAP_list in class_mAP.items(): # noqa: N816\n",
" plt.plot(perturbation_values, class_mAP_list, label=baseline[0].names[class_idx])\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "3aef482b-1a2b-4b2e-b522-7032776320d2",
"metadata": {},
"source": [
"The most evident detail here, as in the previous graph, is that the trends are not strictly downwards. Occasionally, an increase in the distortion coefficients can improve object detection. Its possible this would occur when the resulting skew better aligns the orientation of the object with the training data. The particularly aggressive spikes up and down are likely due to a very small dataset, where 1-2 detections can massively swing the relative mAP.\n",
"\n",
"Based on this plot, we can see that the person and motorcycle classes were affected the least. Because radial distortion skews the objects, it is not surprising that smaller objects would be less impacted, given that they would have less total distortion between the minimum and maximum vertices of their bounding boxes."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "23ec21e7-e682-4d08-ad1d-6c42d850402f",
"metadata": {},
"outputs": [
{
"data": {
"image/jpeg": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.title(\"relative mAP values per area\")\n",
"plt.xlabel(\"Radial Distortion Coefficient (k)\")\n",
"plt.ylabel(\"relative mAP\")\n",
"for k in (\"map\", \"map_small\", \"map_medium\"):\n",
" plt.plot(perturbation_values, [m[k].item() for m in perturbed_metrics], label=k)\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "f6e276bd-2eaf-4a4c-a3cd-9bb8c98fa30c",
"metadata": {},
"source": [
"The `map` line covers all sizes; `map_small` and `map_medium` are the mean average precision for objects (smaller than 32^2 pixels, between 32^2 and 96^2 pixels) in area, respectively. (There are no detections in the `map_large` category.) (Here, the mAP value is averaged over a **range** of IoU thresholds, between 0.5 and 0.95.)\n",
"\n",
"These results further reinforce our previous conclusion that smaller objects would be less impacted by the radial distortion. It also demonstrates how additional data points make the downward trend more evident and result in less dramatic spikes in precision.\n"
]
},
{
"cell_type": "markdown",
"id": "b28b9f2a-7217-4427-9c4f-f84656a4dcf2",
"metadata": {},
"source": [
"## End of Notebook"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.15"
}
},
"nbformat": 4,
"nbformat_minor": 5
}