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+ "_model_module_version": "1.5.0",
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+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "view-in-github",
+ "colab_type": "text"
+ },
+ "source": [
+ "![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\")
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Set-up environment\n",
+ "\n",
+ "We'll first install 🤗 Transformers (from Github as it's not yet included in a new release) and decord, which we'll use to decode a video."
+ ],
+ "metadata": {
+ "id": "hSHCiig6MCtC"
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "5X6zy1c5L6sy",
+ "outputId": "456989f6-bfc1-414e-f3ba-a35cb779b953"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+ " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+ " Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install -q git+https://github.com/huggingface/transformers.git"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!pip install -q decord"
+ ],
+ "metadata": {
+ "id": "4_6cm80vMyy-"
+ },
+ "execution_count": 2,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Load video\n",
+ "\n",
+ "Here we load a video of people eating spaghetti."
+ ],
+ "metadata": {
+ "id": "z7Bcj5J1MEL1"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from huggingface_hub import hf_hub_download\n",
+ "from ipywidgets import Video\n",
+ "\n",
+ "file_path = hf_hub_download(\n",
+ " repo_id=\"nielsr/video-demo\", filename=\"eating_spaghetti.mp4\", repo_type=\"dataset\"\n",
+ ")\n",
+ "Video.from_file(file_path, width=500)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 306,
+ "referenced_widgets": [
+ "321c2e40c6394ea3ad0d46cdcd265d8f",
+ "87d29fba2c714fe39e1f9787112e0448"
+ ]
+ },
+ "id": "xExRsm5dM53A",
+ "outputId": "e03852ac-b826-48bd-e391-4482be5c0b27"
+ },
+ "execution_count": 3,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Video(value=b'\\x00\\x00\\x00 ftypisom\\x00\\x00\\x02\\x00isomiso2avc1mp41\\x00\\x00\\x00\\x08free\\x00\\x0fI\\xb7mdat\\x00\\x…"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "321c2e40c6394ea3ad0d46cdcd265d8f"
+ }
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "We'll sample 8 frames from the video."
+ ],
+ "metadata": {
+ "id": "LL8sKy_rNuCO"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from decord import VideoReader, cpu\n",
+ "import numpy as np\n",
+ "\n",
+ "np.random.seed(0)\n",
+ "\n",
+ "def sample_frame_indices(clip_len, frame_sample_rate, seg_len):\n",
+ " converted_len = int(clip_len * frame_sample_rate)\n",
+ " end_idx = np.random.randint(converted_len, seg_len)\n",
+ " start_idx = end_idx - converted_len\n",
+ " indices = np.linspace(start_idx, end_idx, num=clip_len)\n",
+ " indices = np.clip(indices, start_idx, end_idx - 1).astype(np.int64)\n",
+ " return indices\n",
+ "\n",
+ "vr = VideoReader(file_path, num_threads=1, ctx=cpu(0))\n",
+ "\n",
+ "# sample 16 frames\n",
+ "vr.seek(0)\n",
+ "indices = sample_frame_indices(clip_len=8, frame_sample_rate=1, seg_len=len(vr))\n",
+ "video = vr.get_batch(indices).asnumpy()\n",
+ "print(video.shape)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "is1p-s13MVyS",
+ "outputId": "0c35f6bc-5f68-46d0-ef93-a007362971dc"
+ },
+ "execution_count": 4,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "(8, 360, 640, 3)\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Run inference\n",
+ "\n",
+ "Finally, we forward the video + 3 possible texts through the X-CLIP model. The model will tell us how much each text matches with the given video."
+ ],
+ "metadata": {
+ "id": "3qB8DlXHMV-p"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from transformers import XCLIPProcessor, XCLIPModel\n",
+ "import torch\n",
+ "\n",
+ "model_name = \"microsoft/xclip-base-patch32\"\n",
+ "processor = XCLIPProcessor.from_pretrained(model_name)\n",
+ "model = XCLIPModel.from_pretrained(model_name)\n",
+ "\n",
+ "inputs = processor(text=[\"playing sports\", \"eating spaghetti\", \"go shopping\"], videos=list(video), return_tensors=\"pt\", padding=True)\n",
+ "\n",
+ "# forward pass\n",
+ "with torch.no_grad():\n",
+ " outputs = model(**inputs)\n",
+ "\n",
+ "probs = outputs.logits_per_video.softmax(dim=1)\n",
+ "probs"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 291,
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+ },
+ "id": "FZV0SpApMCUz",
+ "outputId": "b3c4a1b4-0aa2-42b3-ef4b-970af769f10d"
+ },
+ "execution_count": 5,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Downloading: 0%| | 0.00/380 [00:00"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Set-up environment\n",
+ "\n",
+ "We first install 🤗 Transformers, decord and pytube."
+ ],
+ "metadata": {
+ "id": "uOK4lJnqF7Um"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!pip install -q git+https://github.com/huggingface/transformers.git decord"
+ ],
+ "metadata": {
+ "id": "D9s5zDETZALJ",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "7122f6fc-17f5-4f10-aea7-25d4989776d9"
+ },
+ "execution_count": 1,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+ " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+ " Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n",
+ "\u001b[K |████████████████████████████████| 13.6 MB 34.6 MB/s \n",
+ "\u001b[K |████████████████████████████████| 120 kB 61.6 MB/s \n",
+ "\u001b[K |████████████████████████████████| 6.6 MB 51.5 MB/s \n",
+ "\u001b[?25h Building wheel for transformers (PEP 517) ... \u001b[?25l\u001b[?25hdone\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!pip install -q pytube"
+ ],
+ "metadata": {
+ "id": "rEqyBjsAF6Gt",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "517e0905-d069-46aa-de0b-927ccfa9563a"
+ },
+ "execution_count": 2,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\u001b[?25l\r\u001b[K |█████▉ | 10 kB 30.0 MB/s eta 0:00:01\r\u001b[K |███████████▋ | 20 kB 35.3 MB/s eta 0:00:01\r\u001b[K |█████████████████▍ | 30 kB 43.1 MB/s eta 0:00:01\r\u001b[K |███████████████████████▏ | 40 kB 37.2 MB/s eta 0:00:01\r\u001b[K |█████████████████████████████ | 51 kB 40.5 MB/s eta 0:00:01\r\u001b[K |████████████████████████████████| 56 kB 4.1 MB/s \n",
+ "\u001b[?25h"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Load video\n",
+ "\n",
+ "Here you can provide any YouTube video you like! Just provide the URL :) in my case, I'm providing a YouTube video of Karpathy teaching neural networks."
+ ],
+ "metadata": {
+ "id": "mMGm2YT-F-I0"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from pytube import YouTube\n",
+ "\n",
+ "youtube_url = 'https://youtu.be/VMj-3S1tku0'\n",
+ "yt = YouTube(youtube_url)\n",
+ "\n",
+ "streams = yt.streams.filter(file_extension='mp4')\n",
+ "print(streams)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "URjoq_L8GRRr",
+ "outputId": "3346b7f2-f8e0-4631-878b-b02e6350e5b5"
+ },
+ "execution_count": 3,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "[, , , , , , , , , ]\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "len(streams)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "fZqKyZyJHtmY",
+ "outputId": "5df56ccc-5561-49c7-977d-92972146bf97"
+ },
+ "execution_count": 4,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "10"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 4
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "file_path = streams[0].download()"
+ ],
+ "metadata": {
+ "id": "niEVCb6GHHxs"
+ },
+ "execution_count": 5,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Sample frames\n",
+ "\n",
+ "The X-CLIP model we'll use expects 32 frames for a given video. Let's sample them:"
+ ],
+ "metadata": {
+ "id": "efsMb2d0IoIN"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from decord import VideoReader, cpu\n",
+ "import torch\n",
+ "import numpy as np\n",
+ "\n",
+ "from huggingface_hub import hf_hub_download\n",
+ "\n",
+ "np.random.seed(0)\n",
+ "\n",
+ "def sample_frame_indices(clip_len, frame_sample_rate, seg_len):\n",
+ " converted_len = int(clip_len * frame_sample_rate)\n",
+ " end_idx = np.random.randint(converted_len, seg_len)\n",
+ " start_idx = end_idx - converted_len\n",
+ " indices = np.linspace(start_idx, end_idx, num=clip_len)\n",
+ " indices = np.clip(indices, start_idx, end_idx - 1).astype(np.int64)\n",
+ " return indices\n",
+ "\n",
+ "videoreader = VideoReader(file_path, num_threads=1, ctx=cpu(0))\n",
+ "\n",
+ "# sample 32 frames\n",
+ "videoreader.seek(0)\n",
+ "indices = sample_frame_indices(clip_len=32, frame_sample_rate=4, seg_len=len(videoreader))\n",
+ "video = videoreader.get_batch(indices).asnumpy()"
+ ],
+ "metadata": {
+ "id": "idX9AJvcDyKJ"
+ },
+ "execution_count": 6,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "video.shape"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "WOQwqVlkySBC",
+ "outputId": "09759579-3cf8-4568-bb96-2b09a9a9abd6"
+ },
+ "execution_count": 7,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "(32, 360, 640, 3)"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 7
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Let's visualize the first of the 32 frames!"
+ ],
+ "metadata": {
+ "id": "A7JN-NlaIl_x"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from PIL import Image\n",
+ "\n",
+ "Image.fromarray(video[0])"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 377
+ },
+ "id": "hL-shDBOH3H-",
+ "outputId": "9a8233b4-64af-4fac-e15a-b1b7f9eb3b69"
+ },
+ "execution_count": 8,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {},
+ "execution_count": 8
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Load X-CLIP model\n",
+ "\n",
+ "Let's instantiate the XCLIP model, along with its processor."
+ ],
+ "metadata": {
+ "id": "Vkm3ZVqqH1VB"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from transformers import XCLIPProcessor, XCLIPModel\n",
+ "\n",
+ "model_name = \"microsoft/xclip-base-patch16-zero-shot\"\n",
+ "processor = XCLIPProcessor.from_pretrained(model_name)\n",
+ "model = XCLIPModel.from_pretrained(model_name)"
+ ],
+ "metadata": {
+ "id": "GccWJWYvzYwh",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 361,
+ "referenced_widgets": [
+ "b5ce997dab0b42bd8b98243ac224e492",
+ "889870dff4bd45d090736c0017d15487",
+ "447e4740619648d288f68a71d9d8bc04",
+ "d49188c5431a46fcbc5a3063db509b49",
+ "a9059125a94a48869118c55be3be429b",
+ "591c8ba6910348ff8558fbd418bc83e3",
+ "cf44028226fa492ea80cbb799a6ae6d3",
+ "ee62c56d9fee4be29eb9f3c072e869bf",
+ "8499de6f936642cb975ad1f897b66580",
+ "7656548232014734821ef0d3497772cd",
+ "97adc9e6a25e4c9b818160ce74ae754e",
+ "c1b66a82c3d6443d87cf27aa0e11a6fd",
+ "fa4db0b3cc18444dbca2e92c5ae36368",
+ "786d0a660f414c5f8bcfece540e703f5",
+ "4ec94014eeb54fd4960ea305e63f3242",
+ "1546aaab9cd245dc8e963610b2fd9bb6",
+ "486cca6385cc4227bd02ead23d5f5d5b",
+ "173687d88e454d5ea72d2e3e0ea86eba",
+ "409d478913f242fe82c3fac8fbdf2964",
+ "ba8f5cc79ea64618992b323f7ed64072",
+ "e8d2368e5eda42af8069823622f2fa3f",
+ "8a188b9ff645490c89535ac21fc22f04",
+ "8112fcedd90b4f789ced3c9550713769",
+ "bc2f2f644dfd4d3e84cc9ac275c5c622",
+ "a3e6fc050cad4f0f93d5bbb42251683c",
+ "66ab984a74e049e4a5be2aecefa52bb8",
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+ ]
+ },
+ "outputId": "37b62a80-1622-4c01-82ec-f5de8838c7e8"
+ },
+ "execution_count": 9,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Moving 0 files to the new cache system\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "0it [00:00, ?it/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "b5ce997dab0b42bd8b98243ac224e492"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Downloading: 0%| | 0.00/310 [00:00