102 lines
2.7 KiB
Plaintext
102 lines
2.7 KiB
Plaintext
{
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"cells": [
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"cell_type": "markdown",
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"**你的目標**是使用光流技術來判斷影片中哪些部分包含向上、向下、向左或向右的移動。\n",
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"\n",
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"首先按照課堂中所述的方法提取影片的幀：\n"
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]
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},
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Code here"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"現在，按照講座中所描述的計算密集光流幀，並將密集光流轉換為極座標：\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Code here"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"為每個光流幀建立方向的直方圖。直方圖顯示有多少向量落入特定的區間，並應該將幀中不同方向的移動分開。\n",
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"\n",
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"> 你可能也需要將所有大小低於某個閾值的向量設為零。這樣可以去除影片中一些小的額外移動，例如眼睛和頭部。\n",
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"\n",
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"繪製一些幀的直方圖。\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Code here"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"看著直方圖，應該可以很直接地判斷移動的方向。你需要選擇那些對應於上/下/左/右方向的區間，並且超過某個閾值的區間。\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Code here"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"恭喜！如果你已完成以上所有步驟，你已完成此實驗！\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n---\n\n**免責聲明**： \n本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。儘管我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。原始語言的文件應被視為權威來源。對於重要信息，建議使用專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋不承擔責任。\n"
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]
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"translation_date": "2025-08-31T09:49:51+00:00",
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"source_file": "lessons/4-ComputerVision/06-IntroCV/lab/MovementDetection.ipynb",
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