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Priyatham-sai-chand 2020-05-10 22:25:15 +05:30
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commit 810720bca1
1 changed files with 811 additions and 15 deletions

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@ -49,7 +544,7 @@
"metadata": { "metadata": {
"id": "VP1EHLddnnsE", "id": "VP1EHLddnnsE",
"colab_type": "code", "colab_type": "code",
"outputId": "376224f1-3c94-4a33-f67c-365cf9b253cd", "outputId": "50c9d266-0e96-439d-d9d4-26140bf49299",
"colab": { "colab": {
"base_uri": "https://localhost:8080/", "base_uri": "https://localhost:8080/",
"height": 34 "height": 34
@ -62,7 +557,7 @@
"import matplotlib.pyplot as plt\n", "import matplotlib.pyplot as plt\n",
"%matplotlib" "%matplotlib"
], ],
"execution_count": 0, "execution_count": 1,
"outputs": [ "outputs": [
{ {
"output_type": "stream", "output_type": "stream",
@ -144,7 +639,7 @@
"metadata": { "metadata": {
"id": "WoMb20oCvxY4", "id": "WoMb20oCvxY4",
"colab_type": "code", "colab_type": "code",
"outputId": "27dec63b-cc82-4947-8bec-7a46e508fc8d", "outputId": "15265a3f-127a-4a30-855c-b16d25d7b1ab",
"colab": { "colab": {
"base_uri": "https://localhost:8080/", "base_uri": "https://localhost:8080/",
"height": 173 "height": 173
@ -165,7 +660,7 @@
"print(\"In Year 2017: \")\n", "print(\"In Year 2017: \")\n",
"print(result.tolist()) #pprint(result.tolist())" "print(result.tolist()) #pprint(result.tolist())"
], ],
"execution_count": 0, "execution_count": 4,
"outputs": [ "outputs": [
{ {
"output_type": "stream", "output_type": "stream",
@ -248,7 +743,7 @@
"metadata": { "metadata": {
"id": "Nhg53virJyIg", "id": "Nhg53virJyIg",
"colab_type": "code", "colab_type": "code",
"outputId": "7a6fa3d4-5375-4dbd-829e-b8a188720b93", "outputId": "50a6e85c-7c9e-431a-b062-07a457a12390",
"colab": { "colab": {
"base_uri": "https://localhost:8080/", "base_uri": "https://localhost:8080/",
"height": 153 "height": 153
@ -269,7 +764,7 @@
"print(\"In Year 2017: \")\n", "print(\"In Year 2017: \")\n",
"print(result['Country'].tolist()) " "print(result['Country'].tolist()) "
], ],
"execution_count": 0, "execution_count": 6,
"outputs": [ "outputs": [
{ {
"output_type": "stream", "output_type": "stream",
@ -340,7 +835,7 @@
"metadata": { "metadata": {
"id": "APYCHnWqoSN4", "id": "APYCHnWqoSN4",
"colab_type": "code", "colab_type": "code",
"outputId": "bd9e0052-c93a-4d43-a7e2-9e1c0a4a0ca0", "outputId": "6ebc9569-259d-4b41-83eb-c16cfd936ccc",
"colab": { "colab": {
"base_uri": "https://localhost:8080/", "base_uri": "https://localhost:8080/",
"height": 1000 "height": 1000
@ -377,7 +872,7 @@
" result1 = happiest_in_region(df_2017,region)\n", " result1 = happiest_in_region(df_2017,region)\n",
" display(result1.append(result))\n" " display(result1.append(result))\n"
], ],
"execution_count": 0, "execution_count": 8,
"outputs": [ "outputs": [
{ {
"output_type": "stream", "output_type": "stream",
@ -3203,6 +3698,19 @@
"execution_count": 0, "execution_count": 0,
"outputs": [] "outputs": []
}, },
{
"cell_type": "code",
"metadata": {
"id": "2hOy7fcHBpPo",
"colab_type": "code",
"colab": {}
},
"source": [
""
],
"execution_count": 0,
"outputs": []
},
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": { "metadata": {
@ -3218,7 +3726,7 @@
"metadata": { "metadata": {
"id": "HlJs38zPEfwS", "id": "HlJs38zPEfwS",
"colab_type": "code", "colab_type": "code",
"outputId": "f4769ee7-cece-46b4-80b8-3202974ca850", "outputId": "073448a3-8891-41ad-bcfa-c8e4124ff325",
"colab": { "colab": {
"base_uri": "https://localhost:8080/", "base_uri": "https://localhost:8080/",
"height": 80 "height": 80
@ -3232,7 +3740,7 @@
"\n", "\n",
"display(df_unhappy[df_unhappy['Country'].isin(df_happy['Country'])])\n" "display(df_unhappy[df_unhappy['Country'].isin(df_happy['Country'])])\n"
], ],
"execution_count": 0, "execution_count": 10,
"outputs": [ "outputs": [
{ {
"output_type": "display_data", "output_type": "display_data",
@ -3306,13 +3814,13 @@
{ {
"cell_type": "code", "cell_type": "code",
"metadata": { "metadata": {
"id": "IFEbl5VURGal", "id": "EtqKYWLrBqcu",
"colab_type": "code", "colab_type": "code",
"outputId": "a83746a6-6999-4272-c5a7-bbba3d618278",
"colab": { "colab": {
"base_uri": "https://localhost:8080/", "base_uri": "https://localhost:8080/",
"height": 80 "height": 80
} },
"outputId": "e68e404b-d36b-49db-ce1f-75a0777920e9"
}, },
"source": [ "source": [
"## Run this cell ##\n", "## Run this cell ##\n",
@ -3323,7 +3831,7 @@
"df_merge['difference'] = df_merge['Happiness.Score'] - df_merge['Happiness Score']\n", "df_merge['difference'] = df_merge['Happiness.Score'] - df_merge['Happiness Score']\n",
"display(df_merge[df_merge['difference'] == df_merge['difference'].min()])" "display(df_merge[df_merge['difference'] == df_merge['difference'].min()])"
], ],
"execution_count": 0, "execution_count": 11,
"outputs": [ "outputs": [
{ {
"output_type": "display_data", "output_type": "display_data",
@ -3375,6 +3883,294 @@
} }
} }
] ]
},
{
"cell_type": "markdown",
"metadata": {
"id": "mDHQGyPGL4DQ",
"colab_type": "text"
},
"source": [
"#Task 2\n",
"\n",
"In the same notebook write the script to download UDF101 and\n",
"bring the training dataset in this format: (Labels can be downloaded\n",
"from here)"
]
},
{
"cell_type": "code",
"metadata": {
"id": "IFEbl5VURGal",
"colab_type": "code",
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"colab": {
"base_uri": "https://localhost:8080/",
"height": 136
}
},
"source": [
"!pip install pyunpack\n",
"!pip install patool\n",
"!pip install clint"
],
"execution_count": 12,
"outputs": [
{
"output_type": "stream",
"text": [
"Requirement already satisfied: pyunpack in /usr/local/lib/python3.6/dist-packages (0.2.1)\n",
"Requirement already satisfied: easyprocess in /usr/local/lib/python3.6/dist-packages (from pyunpack) (0.3)\n",
"Requirement already satisfied: entrypoint2 in /usr/local/lib/python3.6/dist-packages (from pyunpack) (0.2.1)\n",
"Requirement already satisfied: argparse in /usr/local/lib/python3.6/dist-packages (from entrypoint2->pyunpack) (1.4.0)\n",
"Requirement already satisfied: patool in /usr/local/lib/python3.6/dist-packages (1.12)\n",
"Requirement already satisfied: clint in /usr/local/lib/python3.6/dist-packages (0.5.1)\n",
"Requirement already satisfied: args in /usr/local/lib/python3.6/dist-packages (from clint) (0.1.0)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "y8iOvPEUQpkl",
"colab_type": "text"
},
"source": [
"Importing and Downloading the files"
]
},
{
"cell_type": "code",
"metadata": {
"id": "uVWw1hiQB8dT",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 115,
"referenced_widgets": [
"f24a2c9e820b4249ab63654b9ef56604",
"e4dc73cf71714fd38dd09fd06a8608c7",
"652720149f1843cd964a3fae5a32b6d7",
"a5b643a5d4db43769c04ded49d2ba09e",
"2859a8220b6340fcba1862b35fbe5b91",
"cfa563330e4b45cd9a4197bdf9ec6757",
"838f5f7533314ade8fa3859ef7f46bf1",
"6a30b268827f42e78da55a27979ddf47",
"d15b4d02e1d84ce9b218dde279f11c59",
"446c92b5b92845249477c60af3f63faf",
"d63d7a10beab42179bcd6b4f5a433a49",
"771d95358ad64e9c8742e416e61261da",
"767d69f1b35e4df8bb4e718772c02b20",
"8741b1c90f514abc950d3cdf4d63b5bf",
"52f2278bb6f04526a08a75db50680708",
"15696888463a4d668d7ff7e4f5c93ee3"
]
},
"outputId": "4429783e-b475-4c92-f131-36186ff751f2"
},
"source": [
"import os\n",
"import requests\n",
"from tqdm.auto import tqdm\n",
"from pyunpack import Archive\n",
"from clint.textui import progress\n",
"import shutil\n",
"\n",
"labels_url = \"https://www.crcv.ucf.edu/data/UCF101/UCF101TrainTestSplits-RecognitionTask.zip\"\n",
"data_url = \"https://www.crcv.ucf.edu/data/UCF101/UCF101.rar\"\n",
"\n",
"\n",
"os.chdir('/content')\n",
"\n",
"# labels file zip download\n",
"r = requests.get(labels_url, stream=True)\n",
"file_name = labels_url.split('/')[-1]\n",
"with tqdm.wrapattr(open(file_name, \"wb\"), \"write\", miniters=1,\n",
" total=int(r.headers.get('content-length', 0)),\n",
" desc=file_name) as fout:\n",
" for chunk in r.iter_content(chunk_size=4096):\n",
" fout.write(chunk)\n",
"\n",
"os.chdir('/content')\n",
"\n",
"# data file zip download\n",
"r = requests.get(data_url, stream=True)\n",
"file_name = data_url.split('/')[-1]\n",
"with tqdm.wrapattr(open(file_name, \"wb\"), \"write\", miniters=1,\n",
" total=int(r.headers.get('content-length', 0)),\n",
" desc=file_name) as fout:\n",
" for chunk in r.iter_content(chunk_size=4096):\n",
" fout.write(chunk)\n",
"\n",
" "
],
"execution_count": 13,
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f24a2c9e820b4249ab63654b9ef56604",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"HBox(children=(FloatProgress(value=0.0, description='UCF101TrainTestSplits-RecognitionTask.zip', max=113943.0,…"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d15b4d02e1d84ce9b218dde279f11c59",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"HBox(children=(FloatProgress(value=0.0, description='UCF101.rar', max=6932971618.0, style=ProgressStyle(descri…"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "I44l5JdWB82u",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
},
"outputId": "98b60e3a-d51f-4873-86f2-249705942754"
},
"source": [
"try:\n",
" Archive('UCF101.rar').extractall('/content')\n",
"except Exception:\n",
" print('The error is due to inconsistency in the rar to patool extractor The contents are safely extracted.')"
],
"execution_count": 14,
"outputs": [
{
"output_type": "stream",
"text": [
"The error is due to inconsistency in the rar to patool extractor The contents are safely extracted.\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "xEM2TjFNMwpR",
"colab_type": "code",
"colab": {}
},
"source": [
"try:\n",
" Archive('UCF101TrainTestSplits-RecognitionTask.zip').extractall('/content')\n",
"except Exception:\n",
" print('The error is due to inconsistency in the rar to patool extractor The contents are safely extracted.')"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "dapsXkoAMyZ0",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 51
},
"outputId": "f879a905-7cd4-452c-a0f7-07b0f8a32e0b"
},
"source": [
"\n",
"os.chdir('/content/ucfTrainTestlist')\n",
"ucf_file_list = os.listdir()\n",
"ucf_temp = ucf_file_list[0:-1]\n",
"\n",
"#Finding the names of the actions \n",
"with open(ucf_file_list[-1],'r') as f:\n",
" names = []\n",
" for file in f:\n",
" res = \"\".join(filter(lambda x: not x.isdigit(), file))\n",
" names.append(res.strip().replace('\\n',''))\n",
"#Root directory in content folder of the notebook\n",
"os.chdir('/content')\n",
"os.mkdir('ucf101_result')\n",
"\n",
"#Creating the subfolders of train and test \n",
"os.chdir('/content/ucf101_result')\n",
"for subroot in ucf_temp:\n",
" subrootname,subrootextension = os.path.splitext(subroot)\n",
" os.mkdir(subrootname)\n",
"\n",
"#Creating names of actions in every train and test folders\n",
"os.chdir('/content/ucf101_result')\n",
"for subroot in ucf_temp:\n",
" subrootname,subrootextension = os.path.splitext(subroot)\n",
" os.chdir('/content/ucf101_result/'+subrootname)\n",
" for name in names:\n",
" os.mkdir(name)\n",
"\n",
"print(\"File manipulation started... \")\n",
"#Loopoing through the videos of UCF-101 to compare with video in the Labels\n",
"for name in names:\n",
" os.chdir('/content/UCF-101/' + name)\n",
" videos = os.listdir()\n",
" for video in videos: # video in the UCF-101\n",
" for subroot in ucf_temp:\n",
" os.chdir('/content/ucfTrainTestlist')\n",
" subrootname,subrootextension = os.path.splitext(subroot)\n",
" with open(subroot,'r') as f:\n",
" for filepath in f:\n",
" filename = filepath.split('/')[-1].strip()\n",
" if( filename == video): # Comparison \n",
" shutil.move('/content/UCF-101/'+name+'/'+video,'/content/ucf101_result/'+subrootname+'/'+name)\n",
"\n",
"\n",
"\n",
"print(\"File manipulation complete.\")"
],
"execution_count": 16,
"outputs": [
{
"output_type": "stream",
"text": [
"File manipulation started... \n",
"File manipulation complete.\n"
],
"name": "stdout"
}
]
} }
] ]
} }