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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "V8i3gjxY85ps",
"outputId": "b5286759-f627-4e7d-89fb-91ced8842cad"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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"Building wheels for collected packages: ffmpy\n",
" Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for ffmpy: filename=ffmpy-0.3.0-py3-none-any.whl size=4711 sha256=13f8ffda7263e49659b8cfa6e64058f5b17b4ea5d25f283bfe79404460f085ff\n",
" Stored in directory: /root/.cache/pip/wheels/ff/5b/59/913b443e7369dc04b61f607a746b6f7d83fb65e2e19fcc958d\n",
"Successfully built ffmpy\n",
"Installing collected packages: rfc3986, pydub, ffmpy, websockets, uc-micro-py, sniffio, python-multipart, pycryptodome, orjson, mdurl, h11, aiofiles, uvicorn, markdown-it-py, linkify-it-py, anyio, starlette, mdit-py-plugins, httpcore, httpx, fastapi, gradio\n",
"Successfully installed aiofiles-23.1.0 anyio-3.6.2 fastapi-0.93.0 ffmpy-0.3.0 gradio-3.20.1 h11-0.14.0 httpcore-0.16.3 httpx-0.23.3 linkify-it-py-2.0.0 markdown-it-py-2.2.0 mdit-py-plugins-0.3.3 mdurl-0.1.2 orjson-3.8.7 pycryptodome-3.17 pydub-0.25.1 python-multipart-0.0.6 rfc3986-1.5.0 sniffio-1.3.0 starlette-0.25.0 uc-micro-py-1.0.1 uvicorn-0.20.0 websockets-10.4\n"
]
}
],
"source": [
"!pip install gradio"
]
},
{
"cell_type": "code",
"source": [
"import gradio as gr\n",
"gr.Interface.load(\n",
" 'huggingface/nlpconnect/vit-gpt2-image-captioning',\n",
" inputs = gr.Image(label=\"Carga una imagen\"),\n",
" title = \"Classificator\",\n",
" description = \"Obtener descripcion por imagen\"\n",
").launch()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 634
},
"id": "TFIAntoh9MCp",
"outputId": "53099e44-244d-41c3-aef8-8a3060baf087"
},
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Fetching model from: https://huggingface.co/nlpconnect/vit-gpt2-image-captioning\n",
"Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
"Note: opening Chrome Inspector may crash demo inside Colab notebooks.\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.Javascript object>"
],
"application/javascript": [
"(async (port, path, width, height, cache, element) => {\n",
" if (!google.colab.kernel.accessAllowed && !cache) {\n",
" return;\n",
" }\n",
" element.appendChild(document.createTextNode(''));\n",
" const url = await google.colab.kernel.proxyPort(port, {cache});\n",
"\n",
" const external_link = document.createElement('div');\n",
" external_link.innerHTML = `\n",
" <div style=\"font-family: monospace; margin-bottom: 0.5rem\">\n",
" Running on <a href=${new URL(path, url).toString()} target=\"_blank\">\n",
" https://localhost:${port}${path}\n",
" </a>\n",
" </div>\n",
" `;\n",
" element.appendChild(external_link);\n",
"\n",
" const iframe = document.createElement('iframe');\n",
" iframe.src = new URL(path, url).toString();\n",
" iframe.height = height;\n",
" iframe.allow = \"autoplay; camera; microphone; clipboard-read; clipboard-write;\"\n",
" iframe.width = width;\n",
" iframe.style.border = 0;\n",
" element.appendChild(iframe);\n",
" })(7860, \"/\", \"100%\", 500, false, window.element)"
]
},
"metadata": {}
},
{
"output_type": "execute_result",
"data": {
"text/plain": []
},
"metadata": {},
"execution_count": 5
}
]
}
]
} |