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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,159 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "faster_coco_eval.__version__='1.5.6'\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import numpy as np\n", | ||
| "import logging\n", | ||
| "import faster_coco_eval\n", | ||
| "from faster_coco_eval import COCO, COCOeval_faster\n", | ||
| "\n", | ||
| "print(f\"{faster_coco_eval.__version__=}\")\n", | ||
| "\n", | ||
| "logging.root.setLevel(\"INFO\")\n", | ||
| "logging.debug(\"Запись.\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "prepared_coco_in_dict = COCO.load_json(\"../tests/lvis_dataset/lvis_val_100.json\")\n", | ||
| "prepared_anns = COCO.load_json(\"../tests/lvis_dataset/lvis_results_100.json\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "iouType = \"segm\"" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "Evaluate annotation type *segm*\n", | ||
| "COCOeval_opt.evaluate() finished...\n", | ||
| "DONE (t=1.43s).\n", | ||
| "Accumulating evaluation results...\n", | ||
| "COCOeval_opt.accumulate() finished...\n", | ||
| "DONE (t=0.39s).\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds=all] = 0.132\n", | ||
| " Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=300 catIds=all] = 0.373\n", | ||
| " Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=300 catIds=all] = 0.069\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=300 catIds=all] = 0.090\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=300 catIds=all] = 0.144\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=300 catIds=all] = 0.204\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds= r] = 0.000\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds= c] = 0.127\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds= f] = 0.134\n", | ||
| " Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds=all] = 0.164\n", | ||
| " Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=300 catIds=all] = 0.109\n", | ||
| " Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=300 catIds=all] = 0.176\n", | ||
| " Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=300 catIds=all] = 0.249\n", | ||
| " Average Recall (AR) @[ IoU=0.50 | area= all | maxDets=300 catIds=all] = 0.449\n", | ||
| " Average Recall (AR) @[ IoU=0.75 | area= all | maxDets=300 catIds=all] = 0.092\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "cocoGt = COCO(prepared_coco_in_dict)\n", | ||
| "cocoDt = cocoGt.loadRes(prepared_anns)\n", | ||
| "\n", | ||
| "cocoEval = COCOeval_faster(cocoGt, cocoDt, iouType, lvis_style=True, print_function=print)\n", | ||
| "cocoEval.params.maxDets = [300]\n", | ||
| "cocoEval.run()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 5, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stderr", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "INFO:lvis.lvis:Loading annotations.\n", | ||
| "INFO:lvis.lvis:Creating index.\n", | ||
| "INFO:lvis.lvis:Index created.\n", | ||
| "INFO:lvis.results:Loading and preparing results.\n", | ||
| "INFO:lvis.results:Creating index.\n", | ||
| "INFO:lvis.results:Index created.\n", | ||
| "INFO:lvis.eval:Running per image evaluation.\n", | ||
| "INFO:lvis.eval:Evaluate annotation type *segm*\n", | ||
| "INFO:lvis.eval:Accumulating evaluation results.\n" | ||
| ] | ||
| }, | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds=all] = 0.132\n", | ||
| " Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=300 catIds=all] = 0.373\n", | ||
| " Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=300 catIds=all] = 0.069\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= s | maxDets=300 catIds=all] = 0.090\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= m | maxDets=300 catIds=all] = 0.144\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= l | maxDets=300 catIds=all] = 0.204\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds= r] = 0.000\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds= c] = 0.127\n", | ||
| " Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds= f] = 0.134\n", | ||
| " Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=300 catIds=all] = 0.164\n", | ||
| " Average Recall (AR) @[ IoU=0.50:0.95 | area= s | maxDets=300 catIds=all] = 0.109\n", | ||
| " Average Recall (AR) @[ IoU=0.50:0.95 | area= m | maxDets=300 catIds=all] = 0.176\n", | ||
| " Average Recall (AR) @[ IoU=0.50:0.95 | area= l | maxDets=300 catIds=all] = 0.249\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from lvis import LVISEval\n", | ||
| "\n", | ||
| "lvis_eval = LVISEval(\"../tests/lvis_dataset/lvis_val_100.json\", \"../tests/lvis_dataset/lvis_results_100.json\", \"segm\")\n", | ||
| "lvis_eval.run()\n", | ||
| "lvis_eval.print_results()" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "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": "3.10.12" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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