Spaces:

IPEC-COMMUNITY
/

openx_dataset_lerobot_v2.0

Running

App Files Files Community

Tavish9 commited on 11 days ago

Commit

39b809b

1 Parent(s): 8aa03f0

add docker file and visualized script

Browse files

Files changed (4) hide show

Dockerfile +31 -0
templates/visualize_dataset_homepage.html +69 -0
templates/visualize_dataset_template.html +459 -0
visualize_dataset_html.py +453 -0

Dockerfile ADDED Viewed

	@@ -0,0 +1,31 @@

+# Configure image
+ARG PYTHON_VERSION=3.10
+FROM python:${PYTHON_VERSION}-slim
+ARG PYTHON_VERSION
+ARG DEBIAN_FRONTEND=noninteractive
+# Install apt dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential cmake git wget \
+    libglib2.0-0 libgl1-mesa-glx libegl1-mesa ffmpeg \
+    && apt-get clean && rm -rf /var/lib/apt/lists/*
+# Create virtual environment
+RUN ln -s /usr/bin/python${PYTHON_VERSION} /usr/bin/python
+RUN python -m venv /opt/venv
+ENV PATH="/opt/venv/bin:$PATH"
+RUN echo "source /opt/venv/bin/activate" >> /root/.bashrc
+RUN useradd -m -u 1000 user
+# Install LeRobot
+RUN git clone https://github.com/huggingface/lerobot.git /lerobot
+WORKDIR /lerobot
+RUN pip install --upgrade --no-cache-dir pip
+RUN pip install --no-cache-dir "." \
+    --extra-index-url https://download.pytorch.org/whl/cpu
+RUN pip install --no-cache-dir flask
+COPY --chown=user . /lerobot
+CMD ["python", "visualize_dataset_html.py", "--host", "0.0.0.0", "--port", "7860"]

templates/visualize_dataset_homepage.html ADDED Viewed

	@@ -0,0 +1,69 @@

+<!-- copy from https://github.com/huggingface/lerobot/blob/main/lerobot/templates/visualize_dataset_homepage.html -->
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Interactive Video Background Page</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+    <script defer src="https://cdn.jsdelivr.net/npm/[email protected]/dist/cdn.min.js"></script>
+</head>
+<body class="h-screen overflow-hidden font-mono text-white" x-data="{
+    inputValue: '',
+    navigateToDataset() {
+        const trimmedValue = this.inputValue.trim();
+        if (trimmedValue) {
+            window.location.href = `/${trimmedValue}`;
+        }
+    }
+}">
+    <div class="fixed inset-0 w-full h-full overflow-hidden">
+        <video class="absolute min-w-full min-h-full w-auto h-auto top-1/2 left-1/2 transform -translate-x-1/2 -translate-y-1/2" autoplay muted loop>
+            <source src="https://huggingface.co/datasets/cadene/koch_bimanual_folding/resolve/v1.6/videos/observation.images.phone_episode_000037.mp4" type="video/mp4">
+            Your browser does not support HTML5 video.
+        </video>
+    </div>
+    <div class="fixed inset-0 bg-black bg-opacity-80"></div>
+    <div class="relative z-10 flex flex-col items-center justify-center h-screen">
+        <div class="text-center mb-8">
+            <h1 class="text-4xl font-bold mb-4">LeRobot Dataset Visualizer</h1>
+            <a href="https://github.com/Tavish9/openx2lerobot" target="_blank" rel="noopener noreferrer" class="underline">create your own datasets</a>
+            <p class="text-xl mb-4"></p>
+            <div class="text-left inline-block">
+                <h3 class="font-semibold mb-2 mt-4">Example Datasets:</h3>
+                <ul class="list-disc list-inside">
+                    {% for dataset in featured_datasets %}
+                        <li><a href="/{{ dataset }}" class="text-blue-300 hover:text-blue-100 hover:underline">{{ dataset }}</a></li>
+                    {% endfor %}
+                </ul>
+            </div>
+        </div>
+        <div class="flex w-full max-w-lg px-4 mb-4">
+            <input
+                type="text"
+                x-model="inputValue"
+                @keyup.enter="navigateToDataset"
+                placeholder="enter dataset id (ex: IPEC-COMMUNITY/jaco_play_lerobot)"
+                class="flex-grow px-4 py-2 rounded-l bg-white bg-opacity-20 text-white placeholder-gray-300 focus:outline-none focus:ring-2 focus:ring-blue-300"
+            >
+            <button
+                @click="navigateToDataset"
+                class="px-4 py-2 bg-blue-500 text-white rounded-r hover:bg-blue-600 focus:outline-none focus:ring-2 focus:ring-blue-300"
+            >
+                Go
+            </button>
+        </div>
+        <details class="mt-4 max-w-full px-4">
+            <summary>More example datasets</summary>
+            <ul class="list-disc list-inside max-h-28 overflow-y-auto break-all">
+                {% for dataset in lerobot_datasets %}
+                    <li><a href="/{{ dataset }}" class="text-blue-300 hover:text-blue-100 hover:underline">{{ dataset }}</a></li>
+                {% endfor %}
+            </ul>
+        </details>
+    </div>
+</body>
+</html>

templates/visualize_dataset_template.html ADDED Viewed

	@@ -0,0 +1,459 @@

+<!-- copy from https://github.com/huggingface/lerobot/blob/main/lerobot/templates/visualize_dataset_template.html -->
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <!-- # TODO(rcadene, mishig25): store the js files locally -->
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/alpinejs/3.13.5/cdn.min.js" defer></script>
+    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/dygraph.min.js" type="text/javascript"></script>
+    <script src="https://cdn.tailwindcss.com"></script>
+    <title>{{ dataset_info.repo_id }} episode {{ episode_id }}</title>
+</head>
+<!-- Use [Alpin.js](https://alpinejs.dev), a lightweight and easy to learn JS framework -->
+<!-- Use [tailwindcss](https://tailwindcss.com/), CSS classes for styling html -->
+<!-- Use [dygraphs](https://dygraphs.com/), a lightweight JS charting library -->
+<body class="flex flex-col md:flex-row h-screen max-h-screen bg-slate-950 text-gray-200" x-data="createAlpineData()" @keydown.window="(e) => {
+    // Use the space bar to play and pause, instead of default action (e.g. scrolling)
+    const { keyCode, key } = e;
+    if (keyCode === 32 || key === ' ') {
+        e.preventDefault();
+        $refs.btnPause.classList.contains('hidden') ? $refs.btnPlay.click() : $refs.btnPause.click();
+    }else if (key === 'ArrowDown' || key === 'ArrowUp'){
+        const nextEpisodeId = key === 'ArrowDown' ? {{ episode_id }} + 1 : {{ episode_id }} - 1;
+        const lowestEpisodeId = {{ episodes }}.at(0);
+        const highestEpisodeId = {{ episodes }}.at(-1);
+        if(nextEpisodeId >= lowestEpisodeId && nextEpisodeId <= highestEpisodeId){
+            window.location.href = `./episode_${nextEpisodeId}`;
+        }
+    }
+}">
+    <!-- Sidebar -->
+    <div x-ref="sidebar" class="bg-slate-900 p-5 break-words overflow-y-auto shrink-0 md:shrink md:w-60 md:max-h-screen">
+        <a href="https://github.com/huggingface/lerobot" target="_blank" class="hidden md:block">
+            <img src="https://github.com/huggingface/lerobot/raw/main/media/lerobot-logo-thumbnail.png">
+        </a>
+        <a href="https://huggingface.co/datasets/{{ dataset_info.repo_id }}" target="_blank">
+            <h1 class="mb-4 text-xl font-semibold">{{ dataset_info.repo_id }}</h1>
+        </a>
+        <ul>
+            <li>
+                Number of samples/frames: {{ dataset_info.num_samples }}
+            </li>
+            <li>
+                Number of episodes: {{ dataset_info.num_episodes }}
+            </li>
+            <li>
+                Frames per second: {{ dataset_info.fps }}
+            </li>
+        </ul>
+        <p>Episodes:</p>
+        <!-- episodes menu for medium & large screens -->
+        <ul class="ml-2 hidden md:block">
+            {% for episode in episodes %}
+            <li class="font-mono text-sm mt-0.5">
+                <a href="episode_{{ episode }}" class="underline {% if episode_id == episode %}font-bold -ml-1{% endif %}">
+                    Episode {{ episode }}
+                </a>
+            </li>
+            {% endfor %}
+        </ul>
+        <!-- episodes menu for small screens -->
+        <div class="flex overflow-x-auto md:hidden">
+            {% for episode in episodes %}
+            <p class="font-mono text-sm mt-0.5 border-r last:border-r-0 px-2 {% if episode_id == episode %}font-bold{% endif %}">
+                <a href="episode_{{ episode }}" class="">
+                    {{ episode }}
+                </a>
+            </p>
+            {% endfor %}
+        </div>
+    </div>
+    <!-- Toggle sidebar button -->
+    <button class="flex items-center opacity-50 hover:opacity-100 mx-1 hidden md:block"
+        @click="() => ($refs.sidebar.classList.toggle('hidden'))" title="Toggle sidebar">
+        <div class="bg-slate-500 w-2 h-10 rounded-full"></div>
+    </button>
+    <!-- Content -->
+    <div class="max-h-screen flex flex-col gap-4 overflow-y-auto md:flex-1">
+        <h1 class="text-xl font-bold mt-4 font-mono">
+            Episode {{ episode_id }}
+        </h1>
+        <!-- Error message -->
+        <div class="font-medium text-orange-700 hidden" :class="{ 'hidden': !videoCodecError }">
+            <p>Videos could NOT play because <a href="https://en.wikipedia.org/wiki/AV1" target="_blank" class="underline">AV1</a> decoding is not available on your browser.</p>
+            <ul class="list-decimal list-inside">
+                <li>If iPhone: <span class="italic">It is supported with A17 chip or higher.</span></li>
+                <li>If Mac with Safari: <span class="italic">It is supported on most browsers except Safari with M1 chip or higher and on Safari with M3 chip or higher.</span></li>
+                <li>Other: <span class="italic">Contact the maintainers on LeRobot discord channel:</span> <a href="https://discord.com/invite/s3KuuzsPFb" target="_blank" class="underline">https://discord.com/invite/s3KuuzsPFb</a></li>
+            </ul>
+        </div>
+        <!-- Videos -->
+        <div  class="max-w-32 relative text-sm mb-4 select-none"
+            @click.outside="isVideosDropdownOpen = false">
+            <div
+                @click="isVideosDropdownOpen = !isVideosDropdownOpen"
+                class="p-2 border border-slate-500 rounded flex justify-between items-center cursor-pointer"
+            >
+            <span class="truncate">filter videos</span>
+            <div class="transition-transform" :class="{ 'rotate-180': isVideosDropdownOpen }">🔽</div>
+            </div>
+            <div x-show="isVideosDropdownOpen"
+                class="absolute mt-1 border border-slate-500 rounded shadow-lg z-10">
+            <div>
+                <template x-for="option in videosKeys" :key="option">
+                <div
+                    @click="videosKeysSelected = videosKeysSelected.includes(option) ? videosKeysSelected.filter(v => v !== option) : [...videosKeysSelected, option]"
+                    class="p-2 cursor-pointer bg-slate-900"
+                    :class="{ 'bg-slate-700': videosKeysSelected.includes(option) }"
+                    x-text="option"
+                ></div>
+                </template>
+            </div>
+            </div>
+        </div>
+        <div class="flex flex-wrap gap-x-2 gap-y-6">
+            {% for video_info in videos_info %}
+            <div x-show="!videoCodecError && videosKeysSelected.includes('{{ video_info.filename }}')" class="max-w-96 relative">
+                <p class="absolute inset-x-0 -top-4 text-sm text-gray-300 bg-gray-800 px-2 rounded-t-xl truncate">{{ video_info.filename }}</p>
+                <video muted loop type="video/mp4" class="object-contain w-full h-full" @canplaythrough="videoCanPlay" @timeupdate="() => {
+                    if (video.duration) {
+                      const time = video.currentTime;
+                      const pc = (100 / video.duration) * time;
+                      $refs.slider.value = pc;
+                      dygraphTime = time;
+                      dygraphIndex = Math.floor(pc * dygraph.numRows() / 100);
+                      dygraph.setSelection(dygraphIndex, undefined, true, true);
+                      $refs.timer.textContent = formatTime(time) + ' / ' + formatTime(video.duration);
+                      updateTimeQuery(time.toFixed(2));
+                    }
+                }" @ended="() => {
+                    $refs.btnPlay.classList.remove('hidden');
+                    $refs.btnPause.classList.add('hidden');
+                }"
+                    @loadedmetadata="() => ($refs.timer.textContent = formatTime(0) + ' / ' + formatTime(video.duration))">
+                    <source src="{{ video_info.url }}">
+                    Your browser does not support the video tag.
+                </video>
+            </div>
+            {% endfor %}
+        </div>
+        <!-- Language instruction -->
+        {% if videos_info[0].language_instruction %}
+        <p class="font-medium mt-2">
+            Language Instruction: <span class="italic">{{ videos_info[0].language_instruction }}</span>
+        </p>
+        {% endif %}
+        <!-- Shortcuts info -->
+        <div class="text-sm hidden md:block">
+            Hotkeys: <span class="font-mono">Space</span> to pause/unpause, <span class="font-mono">Arrow Down</span> to go to next episode, <span class="font-mono">Arrow Up</span> to go to previous episode.
+        </div>
+        <!-- Controllers -->
+        <div class="flex gap-1 text-3xl items-center">
+            <button x-ref="btnPlay" class="-rotate-90" class="-rotate-90" title="Play. Toggle with Space" @click="() => {
+                videos.forEach(video => video.play());
+                $refs.btnPlay.classList.toggle('hidden');
+                $refs.btnPause.classList.toggle('hidden');
+            }">🔽</button>
+            <button x-ref="btnPause" class="hidden" title="Pause. Toggle with Space" @click="() => {
+                videos.forEach(video => video.pause());
+                $refs.btnPlay.classList.toggle('hidden');
+                $refs.btnPause.classList.toggle('hidden');
+            }">⏸️</button>
+            <button title="Jump backward 5 seconds"
+                @click="() => (videos.forEach(video => (video.currentTime -= 5)))">⏪</button>
+            <button title="Jump forward 5 seconds"
+                @click="() => (videos.forEach(video => (video.currentTime += 5)))">⏩</button>
+            <button title="Rewind from start"
+                @click="() => (videos.forEach(video => (video.currentTime = 0.0)))">↩️</button>
+            <input x-ref="slider" max="100" min="0" step="1" type="range" value="0" class="w-80 mx-2" @input="() => {
+                const sliderValue = $refs.slider.value;
+                videos.forEach(video => {
+                    const time = (video.duration * sliderValue) / 100;
+                    video.currentTime = time;
+                });
+            }" />
+            <div x-ref="timer" class="font-mono text-sm border border-slate-500 rounded-lg px-1 py-0.5 shrink-0">0:00 /
+                0:00
+            </div>
+        </div>
+        <!-- Graph -->
+        <div class="flex gap-2 mb-4 flex-wrap">
+            <div>
+                <div id="graph" @mouseleave="() => {
+                    dygraph.setSelection(dygraphIndex, undefined, true, true);
+                    dygraphTime = video.currentTime;
+                }">
+                </div>
+                <p x-ref="graphTimer" class="font-mono ml-14 mt-4"
+                    x-init="$watch('dygraphTime', value => ($refs.graphTimer.innerText = `Time: ${dygraphTime.toFixed(2)}s`))">
+                    Time: 0.00s
+                </p>
+            </div>
+            <table class="text-sm border-collapse border border-slate-700" x-show="currentFrameData">
+                <thead>
+                    <tr>
+                        <th></th>
+                        <template x-for="(_, colIndex) in Array.from({length: columns.length}, (_, index) => index)">
+                            <th class="border border-slate-700">
+                                <div class="flex gap-x-2 justify-between px-2">
+                                    <input type="checkbox" :checked="isColumnChecked(colIndex)"
+                                        @change="toggleColumn(colIndex)">
+                                    <p x-text="`${columns[colIndex].key}`"></p>
+                                </div>
+                            </th>
+                        </template>
+                    </tr>
+                </thead>
+                <tbody>
+                    <template x-for="(row, rowIndex) in rows">
+                        <tr class="odd:bg-gray-800 even:bg-gray-900">
+                            <td class="border border-slate-700">
+                                <div class="flex gap-x-2 max-w-64 font-semibold px-1 break-all">
+                                    <input type="checkbox" :checked="isRowChecked(rowIndex)"
+                                        @change="toggleRow(rowIndex)">
+                                    <p x-text="`${rowLabels[rowIndex]}`"></p>
+                                </div>
+                            </td>
+                            <template x-for="(cell, colIndex) in row">
+                                <td x-show="cell" class="border border-slate-700">
+                                    <div class="flex gap-x-2 w-24 justify-between px-2" :class="{ 'hidden': cell.isNull }">
+                                        <input type="checkbox" x-model="cell.checked" @change="updateTableValues()">
+                                        <span x-text="`${!cell.isNull ? cell.value.toFixed(2) : null}`"
+                                            :style="`color: ${cell.color}`"></span>
+                                    </div>
+                                </td>
+                            </template>
+                        </tr>
+                    </template>
+                </tbody>
+            </table>
+            <div id="labels" class="hidden">
+            </div>
+        </div>
+    </div>
+    <script>
+        const parentOrigin = "https://huggingface.co";
+        const searchParams = new URLSearchParams();
+        searchParams.set("dataset", "{{ dataset_info.repo_id }}");
+        searchParams.set("episode", "{{ episode_id }}");
+		window.parent.postMessage({ queryString: searchParams.toString() }, parentOrigin);
+    </script>
+    <script>
+        function createAlpineData() {
+            return {
+                // state
+                dygraph: null,
+                currentFrameData: null,
+                checked: [],
+                dygraphTime: 0.0,
+                dygraphIndex: 0,
+                videos: null,
+                video: null,
+                colors: null,
+                nVideos: {{ videos_info | length }},
+                nVideoReadyToPlay: 0,
+                videoCodecError: false,
+                isVideosDropdownOpen: false,
+                videosKeys: {{ videos_info | map(attribute='filename') | list | tojson }},
+                videosKeysSelected: [],
+                columns: {{ columns | tojson }},
+                rowLabels: {{ columns | tojson }}.reduce((colA, colB) => colA.value.length > colB.value.length ? colA : colB).value,
+                // alpine initialization
+                init() {
+                    // check if videos can play
+                    const dummyVideo = document.createElement('video');
+                    const canPlayVideos = dummyVideo.canPlayType('video/mp4; codecs="av01.0.05M.08"'); // codec source: https://huggingface.co/blog/video-encoding#results
+                    if(!canPlayVideos){
+                        this.videoCodecError = true;
+                    }
+                    this.videosKeysSelected = this.videosKeys.map(opt => opt)
+                    // process CSV data
+                    const csvDataStr = {{ episode_data_csv_str|tojson|safe }};
+                    // Create a Blob with the CSV data
+                    const blob = new Blob([csvDataStr], { type: 'text/csv;charset=utf-8;' });
+                    // Create a URL for the Blob
+                    const csvUrl = URL.createObjectURL(blob);
+                    // process CSV data
+                    this.videos = document.querySelectorAll('video');
+                    this.video = this.videos[0];
+                    this.dygraph = new Dygraph(document.getElementById("graph"), csvUrl, {
+                        pixelsPerPoint: 0.01,
+                        legend: 'always',
+                        labelsDiv: document.getElementById('labels'),
+                        labelsKMB: true,
+                        strokeWidth: 1.5,
+                        pointClickCallback: (event, point) => {
+                            this.dygraphTime = point.xval;
+                            this.updateTableValues(this.dygraphTime);
+                        },
+                        highlightCallback: (event, x, points, row, seriesName) => {
+                            this.dygraphTime = x;
+                            this.updateTableValues(this.dygraphTime);
+                        },
+                        drawCallback: (dygraph, is_initial) => {
+                            if (is_initial) {
+                                // dygraph initialization
+                                this.dygraph.setSelection(this.dygraphIndex, undefined, true, true);
+                                this.colors = this.dygraph.getColors();
+                                this.checked = Array(this.colors.length).fill(true);
+                                const colors = [];
+                                let lightness = 30; // const LIGHTNESS = [30, 65, 85]; // state_lightness, action_lightness, pred_action_lightness
+                                for(const column of this.columns){
+                                    const nValues = column.value.length;
+                                    for (let hue = 0; hue < 360; hue += parseInt(360/nValues)) {
+                                        const color = `hsl(${hue}, 100%, ${lightness}%)`;
+                                        colors.push(color);
+                                    }
+                                    lightness += 35;
+                                }
+                                this.dygraph.updateOptions({ colors });
+                                this.colors = colors;
+                                this.updateTableValues();
+                                let url = new URL(window.location.href);
+                                let params = new URLSearchParams(url.search);
+                                let time = params.get("t");
+                                if(time){
+                                    time = parseFloat(time);
+                                    this.videos.forEach(video => (video.currentTime = time));
+                                }
+                            }
+                        },
+                    });
+                },
+                //#region Table Data
+                // turn dygraph's 1D data (at a given time t) to 2D data that whose columns names are defined in this.columnNames.
+                // 2d data view is used to create html table element.
+                get rows() {
+                    if (!this.currentFrameData) {
+                        return [];
+                    }
+                    const rows = [];
+                    const nRows = Math.max(...this.columns.map(column => column.value.length));
+                    let rowIndex = 0;
+                    while(rowIndex < nRows){
+                        const row = [];
+                        // number of states may NOT match number of actions. In this case, we null-pad the 2D array to make a fully rectangular 2d array
+                        const nullCell = { isNull: true };
+                        // row consists of [state value, action value]
+                        let idx = rowIndex;
+                        for(const column of this.columns){
+                            const nColumn = column.value.length;
+                            row.push(rowIndex < nColumn ? this.currentFrameData[idx] : nullCell);
+                            idx += nColumn; // because this.currentFrameData = [state0, state1, ..., stateN, action0, action1, ..., actionN]
+                        }
+                        rowIndex += 1;
+                        rows.push(row);
+                    }
+                    return rows;
+                },
+                isRowChecked(rowIndex) {
+                    return this.rows[rowIndex].every(cell => cell && (cell.isNull || cell.checked));
+                },
+                isColumnChecked(colIndex) {
+                    return this.rows.every(row => row[colIndex] && (row[colIndex].isNull || row[colIndex].checked));
+                },
+                toggleRow(rowIndex) {
+                    const newState = !this.isRowChecked(rowIndex);
+                    this.rows[rowIndex].forEach(cell => {
+                        if (cell && !cell.isNull) cell.checked = newState;
+                    });
+                    this.updateTableValues();
+                },
+                toggleColumn(colIndex) {
+                    const newState = !this.isColumnChecked(colIndex);
+                    this.rows.forEach(row => {
+                        if (row[colIndex] && !row[colIndex].isNull) row[colIndex].checked = newState;
+                    });
+                    this.updateTableValues();
+                },
+                // given time t, update the values in the html table with "data[t]"
+                updateTableValues(time) {
+                    if (!this.colors) {
+                        return;
+                    }
+                    let pc = (100 / this.video.duration) * (time === undefined ? this.video.currentTime : time);
+                    if (isNaN(pc)) pc = 0;
+                    const index = Math.floor(pc * this.dygraph.numRows() / 100);
+                    // slice(1) to remove the timestamp point that we do not need
+                    const labels = this.dygraph.getLabels().slice(1);
+                    const values = this.dygraph.rawData_[index].slice(1);
+                    const checkedNew = this.currentFrameData ? this.currentFrameData.map(cell => cell.checked) : Array(
+                        this.colors.length).fill(true);
+                    this.currentFrameData = labels.map((label, idx) => ({
+                        label,
+                        value: values[idx],
+                        color: this.colors[idx],
+                        checked: checkedNew[idx],
+                    }));
+                    const shouldUpdateVisibility = !this.checked.every((value, index) => value === checkedNew[index]);
+                    if (shouldUpdateVisibility) {
+                        this.checked = checkedNew;
+                        this.dygraph.setVisibility(this.checked);
+                    }
+                },
+                //#endregion
+                updateTimeQuery(time) {
+                    let url = new URL(window.location.href);
+                    let params = new URLSearchParams(url.search);
+                    params.set("t", time);
+                    url.search = params.toString();
+                    window.history.replaceState({}, '', url.toString());
+                },
+                formatTime(time) {
+                    var hours = Math.floor(time / 3600);
+                    var minutes = Math.floor((time % 3600) / 60);
+                    var seconds = Math.floor(time % 60);
+                    return (hours > 0 ? hours + ':' : '') + (minutes < 10 ? '0' + minutes : minutes) + ':' + (seconds <
+                        10 ?
+                        '0' + seconds : seconds);
+                },
+                videoCanPlay() {
+                    this.nVideoReadyToPlay += 1;
+                    if(this.nVideoReadyToPlay == this.nVideos) {
+                        // start autoplay all videos in sync
+                        this.$refs.btnPlay.click();
+                    }
+                }
+            };
+        }
+    </script>
+</body>
+</html>

visualize_dataset_html.py ADDED Viewed

	@@ -0,0 +1,453 @@

+#!/usr/bin/env python
+# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" Visualize data of **all** frames of any episode of a dataset of type LeRobotDataset.
+copy from https://github.com/huggingface/lerobot/blob/main/lerobot/scripts/visualize_dataset_html.py
+Note: The last frame of the episode doesnt always correspond to a final state.
+That's because our datasets are composed of transition from state to state up to
+the antepenultimate state associated to the ultimate action to arrive in the final state.
+However, there might not be a transition from a final state to another state.
+Note: This script aims to visualize the data used to train the neural networks.
+~What you see is what you get~. When visualizing image modality, it is often expected to observe
+lossly compression artifacts since these images have been decoded from compressed mp4 videos to
+save disk space. The compression factor applied has been tuned to not affect success rate.
+Example of usage:
+- Visualize data stored on a local machine:
+```bash
+local$ python lerobot/scripts/visualize_dataset_html.py \
+    --repo-id lerobot/pusht
+local$ open http://localhost:9090
+```
+- Visualize data stored on a distant machine with a local viewer:
+```bash
+distant$ python lerobot/scripts/visualize_dataset_html.py \
+    --repo-id lerobot/pusht
+local$ ssh -L 9090:localhost:9090 distant  # create a ssh tunnel
+local$ open http://localhost:9090
+```
+- Select episodes to visualize:
+```bash
+python lerobot/scripts/visualize_dataset_html.py \
+    --repo-id lerobot/pusht \
+    --episodes 7 3 5 1 4
+```
+"""
+import argparse
+import csv
+import json
+import logging
+import re
+import shutil
+import tempfile
+from io import StringIO
+from pathlib import Path
+import numpy as np
+import pandas as pd
+import requests
+from flask import Flask, redirect, render_template, request, url_for
+from huggingface_hub import HfApi
+from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
+from lerobot.common.datasets.utils import IterableNamespace
+from lerobot.common.utils.utils import init_logging
+def available_datasets():
+    api = HfApi()
+    datasets = api.list_datasets(author="IPEC-COMMUNITY", tags=["LeRobot"], filter="modality:video")
+    datasets = [dataset.id for dataset in datasets]
+    return datasets
+def run_server(
+    dataset: LeRobotDataset | IterableNamespace | None,
+    episodes: list[int] | None,
+    host: str,
+    port: str,
+    static_folder: Path,
+    template_folder: Path,
+):
+    app = Flask(__name__, static_folder=static_folder.resolve(), template_folder=template_folder.resolve())
+    app.config["SEND_FILE_MAX_AGE_DEFAULT"] = 0  # specifying not to cache
+    @app.route("/")
+    def hommepage(dataset=dataset):
+        if dataset:
+            dataset_namespace, dataset_name = dataset.repo_id.split("/")
+            return redirect(
+                url_for(
+                    "show_episode",
+                    dataset_namespace=dataset_namespace,
+                    dataset_name=dataset_name,
+                    episode_id=0,
+                )
+            )
+        dataset_param, episode_param = None, None
+        all_params = request.args
+        if "dataset" in all_params:
+            dataset_param = all_params["dataset"]
+        if "episode" in all_params:
+            episode_param = int(all_params["episode"])
+        if dataset_param:
+            dataset_namespace, dataset_name = dataset_param.split("/")
+            return redirect(
+                url_for(
+                    "show_episode",
+                    dataset_namespace=dataset_namespace,
+                    dataset_name=dataset_name,
+                    episode_id=episode_param if episode_param is not None else 0,
+                )
+            )
+        featured_datasets = [
+            "IPEC-COMMUNITY/roboturk_lerobot",
+            "IPEC-COMMUNITY/cmu_play_fusion_lerobot",
+            "IPEC-COMMUNITY/fractal20220817_data_lerobot",
+        ]
+        return render_template(
+            "visualize_dataset_homepage.html",
+            featured_datasets=featured_datasets,
+            lerobot_datasets=available_datasets(),
+        )
+    @app.route("/<string:dataset_namespace>/<string:dataset_name>")
+    def show_first_episode(dataset_namespace, dataset_name):
+        first_episode_id = 0
+        return redirect(
+            url_for(
+                "show_episode",
+                dataset_namespace=dataset_namespace,
+                dataset_name=dataset_name,
+                episode_id=first_episode_id,
+            )
+        )
+    @app.route("/<string:dataset_namespace>/<string:dataset_name>/episode_<int:episode_id>")
+    def show_episode(dataset_namespace, dataset_name, episode_id, dataset=dataset, episodes=episodes):
+        repo_id = f"{dataset_namespace}/{dataset_name}"
+        try:
+            if dataset is None:
+                dataset = get_dataset_info(repo_id)
+        except FileNotFoundError:
+            return (
+                "Make sure to convert your LeRobotDataset to v2 & above. See how to convert your dataset at https://github.com/huggingface/lerobot/pull/461",
+                400,
+            )
+        dataset_version = dataset.meta._version if isinstance(dataset, LeRobotDataset) else dataset.codebase_version
+        match = re.search(r"v(\d+)\.", dataset_version)
+        if match:
+            major_version = int(match.group(1))
+            if major_version < 2:
+                return "Make sure to convert your LeRobotDataset to v2 & above."
+        episode_data_csv_str, columns = get_episode_data(dataset, episode_id)
+        dataset_info = {
+            "repo_id": f"{dataset_namespace}/{dataset_name}",
+            "num_samples": dataset.num_frames if isinstance(dataset, LeRobotDataset) else dataset.total_frames,
+            "num_episodes": dataset.num_episodes if isinstance(dataset, LeRobotDataset) else dataset.total_episodes,
+            "fps": dataset.fps,
+        }
+        if isinstance(dataset, LeRobotDataset):
+            video_paths = [dataset.meta.get_video_file_path(episode_id, key) for key in dataset.meta.video_keys]
+            videos_info = [
+                {"url": url_for("static", filename=video_path), "filename": video_path.parent.name}
+                for video_path in video_paths
+            ]
+            tasks = dataset.meta.episodes[episode_id]["tasks"]
+        else:
+            video_keys = [key for key, ft in dataset.features.items() if ft["dtype"] == "video"]
+            videos_info = [
+                {
+                    "url": f"https://huggingface.co/datasets/{repo_id}/resolve/main/"
+                    + dataset.video_path.format(
+                        episode_chunk=int(episode_id) // dataset.chunks_size,
+                        video_key=video_key,
+                        episode_index=episode_id,
+                    ),
+                    "filename": video_key,
+                }
+                for video_key in video_keys
+            ]
+            response = requests.get(f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/episodes.jsonl")
+            response.raise_for_status()
+            # Split into lines and parse each line as JSON
+            tasks_jsonl = [json.loads(line) for line in response.text.splitlines() if line.strip()]
+            filtered_tasks_jsonl = [row for row in tasks_jsonl if row["episode_index"] == episode_id]
+            tasks = filtered_tasks_jsonl[0]["tasks"]
+        videos_info[0]["language_instruction"] = tasks
+        if episodes is None:
+            episodes = list(
+                range(dataset.num_episodes if isinstance(dataset, LeRobotDataset) else dataset.total_episodes)
+            )
+        return render_template(
+            "visualize_dataset_template.html",
+            episode_id=episode_id,
+            episodes=episodes,
+            dataset_info=dataset_info,
+            videos_info=videos_info,
+            episode_data_csv_str=episode_data_csv_str,
+            columns=columns,
+        )
+    app.run(host=host, port=port)
+def get_ep_csv_fname(episode_id: int):
+    ep_csv_fname = f"episode_{episode_id}.csv"
+    return ep_csv_fname
+def get_episode_data(dataset: LeRobotDataset | IterableNamespace, episode_index):
+    """Get a csv str containing timeseries data of an episode (e.g. state and action).
+    This file will be loaded by Dygraph javascript to plot data in real time."""
+    columns = []
+    selected_columns = [col for col, ft in dataset.features.items() if ft["dtype"] == "float32"]
+    selected_columns.remove("timestamp")
+    # init header of csv with state and action names
+    header = ["timestamp"]
+    for column_name in selected_columns:
+        dim_state = (
+            dataset.meta.shapes[column_name][0]
+            if isinstance(dataset, LeRobotDataset)
+            else dataset.features[column_name].shape[0]
+        )
+        header += [f"{column_name}_{i}" for i in range(dim_state)]
+        if "names" in dataset.features[column_name] and dataset.features[column_name]["names"]:
+            column_names = dataset.features[column_name]["names"]
+            while not isinstance(column_names, list):
+                column_names = list(column_names.values())[0]
+        else:
+            column_names = [f"motor_{i}" for i in range(dim_state)]
+        columns.append({"key": column_name, "value": column_names})
+    selected_columns.insert(0, "timestamp")
+    if isinstance(dataset, LeRobotDataset):
+        from_idx = dataset.episode_data_index["from"][episode_index]
+        to_idx = dataset.episode_data_index["to"][episode_index]
+        data = dataset.hf_dataset.select(range(from_idx, to_idx)).select_columns(selected_columns).with_format("pandas")
+    else:
+        repo_id = dataset.repo_id
+        url = f"https://huggingface.co/datasets/{repo_id}/resolve/main/" + dataset.data_path.format(
+            episode_chunk=int(episode_index) // dataset.chunks_size, episode_index=episode_index
+        )
+        df = pd.read_parquet(url)
+        data = df[selected_columns]  # Select specific columns
+    rows = np.hstack(
+        (
+            np.expand_dims(data["timestamp"], axis=1),
+            *[np.vstack(data[col]) for col in selected_columns[1:]],
+        )
+    ).tolist()
+    # Convert data to CSV string
+    csv_buffer = StringIO()
+    csv_writer = csv.writer(csv_buffer)
+    # Write header
+    csv_writer.writerow(header)
+    # Write data rows
+    csv_writer.writerows(rows)
+    csv_string = csv_buffer.getvalue()
+    return csv_string, columns
+def get_episode_video_paths(dataset: LeRobotDataset, ep_index: int) -> list[str]:
+    # get first frame of episode (hack to get video_path of the episode)
+    first_frame_idx = dataset.episode_data_index["from"][ep_index].item()
+    return [dataset.hf_dataset.select_columns(key)[first_frame_idx][key]["path"] for key in dataset.meta.video_keys]
+def get_episode_language_instruction(dataset: LeRobotDataset, ep_index: int) -> list[str]:
+    # check if the dataset has language instructions
+    if "language_instruction" not in dataset.features:
+        return None
+    # get first frame index
+    first_frame_idx = dataset.episode_data_index["from"][ep_index].item()
+    language_instruction = dataset.hf_dataset[first_frame_idx]["language_instruction"]
+    # TODO (michel-aractingi) hack to get the sentence, some strings in openx are badly stored
+    # with the tf.tensor appearing in the string
+    return language_instruction.removeprefix("tf.Tensor(b'").removesuffix("', shape=(), dtype=string)")
+def get_dataset_info(repo_id: str) -> IterableNamespace:
+    response = requests.get(f"https://huggingface.co/datasets/{repo_id}/resolve/main/meta/info.json")
+    response.raise_for_status()  # Raises an HTTPError for bad responses
+    dataset_info = response.json()
+    dataset_info["repo_id"] = repo_id
+    return IterableNamespace(dataset_info)
+def visualize_dataset_html(
+    dataset: LeRobotDataset | None,
+    episodes: list[int] | None = None,
+    output_dir: Path | None = None,
+    serve: bool = True,
+    host: str = "127.0.0.1",
+    port: int = 9090,
+    force_override: bool = False,
+) -> Path | None:
+    init_logging()
+    template_dir = Path(__file__).resolve().parent / "templates"
+    if output_dir is None:
+        # Create a temporary directory that will be automatically cleaned up
+        output_dir = tempfile.mkdtemp(prefix="lerobot_visualize_dataset_")
+    output_dir = Path(output_dir)
+    if output_dir.exists():
+        if force_override:
+            shutil.rmtree(output_dir)
+        else:
+            logging.info(f"Output directory already exists. Loading from it: '{output_dir}'")
+    output_dir.mkdir(parents=True, exist_ok=True)
+    static_dir = output_dir / "static"
+    static_dir.mkdir(parents=True, exist_ok=True)
+    if dataset is None:
+        if serve:
+            run_server(
+                dataset=None,
+                episodes=None,
+                host=host,
+                port=port,
+                static_folder=static_dir,
+                template_folder=template_dir,
+            )
+    else:
+        # Create a simlink from the dataset video folder containg mp4 files to the output directory
+        # so that the http server can get access to the mp4 files.
+        if isinstance(dataset, LeRobotDataset):
+            ln_videos_dir = static_dir / "videos"
+            if not ln_videos_dir.exists():
+                ln_videos_dir.symlink_to((dataset.root / "videos").resolve())
+        if serve:
+            run_server(dataset, episodes, host, port, static_dir, template_dir)
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--repo-id",
+        type=str,
+        default=None,
+        help="Name of hugging face repositery containing a LeRobotDataset dataset (e.g. `lerobot/pusht` for https://huggingface.co/datasets/lerobot/pusht).",
+    )
+    parser.add_argument(
+        "--local-files-only",
+        type=int,
+        default=0,
+        help="Use local files only. By default, this script will try to fetch the dataset from the hub if it exists.",
+    )
+    parser.add_argument(
+        "--root",
+        type=Path,
+        default=None,
+        help="Root directory for a dataset stored locally (e.g. `--root data`). By default, the dataset will be loaded from hugging face cache folder, or downloaded from the hub if available.",
+    )
+    parser.add_argument(
+        "--load-from-hf-hub",
+        type=int,
+        default=0,
+        help="Load videos and parquet files from HF Hub rather than local system.",
+    )
+    parser.add_argument(
+        "--episodes",
+        type=int,
+        nargs="*",
+        default=None,
+        help="Episode indices to visualize (e.g. `0 1 5 6` to load episodes of index 0, 1, 5 and 6). By default loads all episodes.",
+    )
+    parser.add_argument(
+        "--output-dir",
+        type=Path,
+        default=None,
+        help="Directory path to write html files and kickoff a web server. By default write them to 'outputs/visualize_dataset/REPO_ID'.",
+    )
+    parser.add_argument(
+        "--serve",
+        type=int,
+        default=1,
+        help="Launch web server.",
+    )
+    parser.add_argument(
+        "--host",
+        type=str,
+        default="127.0.0.1",
+        help="Web host used by the http server.",
+    )
+    parser.add_argument(
+        "--port",
+        type=int,
+        default=9090,
+        help="Web port used by the http server.",
+    )
+    parser.add_argument(
+        "--force-override",
+        type=int,
+        default=0,
+        help="Delete the output directory if it exists already.",
+    )
+    args = parser.parse_args()
+    kwargs = vars(args)
+    repo_id = kwargs.pop("repo_id")
+    load_from_hf_hub = kwargs.pop("load_from_hf_hub")
+    root = kwargs.pop("root")
+    local_files_only = kwargs.pop("local_files_only")
+    dataset = None
+    if repo_id:
+        dataset = (
+            LeRobotDataset(repo_id, root=root, local_files_only=local_files_only)
+            if not load_from_hf_hub
+            else get_dataset_info(repo_id)
+        )
+    visualize_dataset_html(dataset, **vars(args))
+if __name__ == "__main__":
+    main()