From 170a095f49637361e350b509e04c9864a9280581 Mon Sep 17 00:00:00 2001 From: TAWSIF AHMED Date: Wed, 10 May 2023 14:31:31 +0600 Subject: [PATCH 1/4] adding gradio UI and fixed example to add download the repo --- .../sample_text_to_3d(Gradio_UI).ipynb | 1706 +++++++++++++++ shap_e/examples/sample_text_to_3d.ipynb | 1925 +++++++++++++++-- 2 files changed, 3509 insertions(+), 122 deletions(-) create mode 100644 shap_e/examples/sample_text_to_3d(Gradio_UI).ipynb diff --git a/shap_e/examples/sample_text_to_3d(Gradio_UI).ipynb b/shap_e/examples/sample_text_to_3d(Gradio_UI).ipynb new file mode 100644 index 00000000..b18b6d45 --- /dev/null +++ b/shap_e/examples/sample_text_to_3d(Gradio_UI).ipynb @@ -0,0 +1,1706 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "gpuType": "T4" + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + }, + "accelerator": "GPU", + "gpuClass": "standard" + }, + "cells": [ + { + "cell_type": "code", + "source": [ + "!pip install torch\n", + "!pip install git+https://github.com/openai/shap-e.git" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "JJQn3gf0xDeB", + "outputId": "9e9ad838-dd0e-4ef7-d03b-b24c790c0a8f" + }, + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.0.0+cu118)\n", + "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.1)\n", + "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch) (4.5.0)\n", + "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.2)\n", + "Requirement already satisfied: sympy in 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latents = sample_latents(\n", + " batch_size=batch_size,\n", + " model=model,\n", + " diffusion=diffusion,\n", + " guidance_scale=guidance_scale,\n", + " model_kwargs=dict(texts=[prompt] * batch_size),\n", + " progress=True,\n", + " clip_denoised=True,\n", + " use_fp16=True,\n", + " use_karras=True,\n", + " karras_steps=64,\n", + " sigma_min=1e-3,\n", + " sigma_max=160,\n", + " s_churn=0,\n", + " )\n", + "\n", + " # Saving the latents as meshes.\n", + " with open(f'example_mesh.ply', 'wb') as f:\n", + " decode_latent_mesh(xm, latents[0]).tri_mesh().write_ply(f)\n", + "\n", + " return \"example_mesh.ply\"\n", + "\n", + "inputs = gr.inputs.Textbox(label=\"Prompt\")\n", + "outputs = gr.outputs.File(label=\"Generated Mesh\")\n", + "gr.Interface(generate_mesh, inputs, outputs).launch()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 784 + }, + "id": "vp2QMmVu2biV", + "outputId": "5b920d4a-deb7-48bc-b84d-6a69c4009b8b" + }, + "execution_count": 12, + 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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": [ + "" + ], + "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", + "
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" + ] + }, + "metadata": {}, + "execution_count": 17 + } + ] + } + ] +} \ No newline at end of file diff --git a/shap_e/examples/sample_text_to_3d.ipynb b/shap_e/examples/sample_text_to_3d.ipynb index ef39d441..4b3e09cd 100644 --- a/shap_e/examples/sample_text_to_3d.ipynb +++ b/shap_e/examples/sample_text_to_3d.ipynb @@ -1,124 +1,1805 @@ { - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "id": "964ccced", - "metadata": {}, - "outputs": [], - "source": [ - "import torch\n", - "\n", - "from shap_e.diffusion.sample import sample_latents\n", - "from shap_e.diffusion.gaussian_diffusion import diffusion_from_config\n", - "from shap_e.models.download import load_model, load_config\n", - "from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget" - ] + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "gpuType": "T4" + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + 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"_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + } + } + } }, - { - "cell_type": "code", - "execution_count": null, - "id": "8eed3a76", - "metadata": {}, - "outputs": [], - "source": [ - "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2d922637", - "metadata": {}, - "outputs": [], - "source": [ - "xm = load_model('transmitter', device=device)\n", - "model = load_model('text300M', device=device)\n", - "diffusion = diffusion_from_config(load_config('diffusion'))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "53d329d0", - "metadata": {}, - "outputs": [], - "source": [ - "batch_size = 4\n", - "guidance_scale = 15.0\n", - "prompt = \"a shark\"\n", - "\n", - "latents = sample_latents(\n", - " batch_size=batch_size,\n", - " model=model,\n", - " diffusion=diffusion,\n", - " guidance_scale=guidance_scale,\n", - " model_kwargs=dict(texts=[prompt] * batch_size),\n", - " progress=True,\n", - " clip_denoised=True,\n", - " use_fp16=True,\n", - " use_karras=True,\n", - " karras_steps=64,\n", - " sigma_min=1e-3,\n", - " sigma_max=160,\n", - " s_churn=0,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "633da2ec", - "metadata": {}, - "outputs": [], - "source": [ - "render_mode = 'nerf' # you can change this to 'stf'\n", - "size = 64 # this is the size of the renders; higher values take longer to render.\n", - "\n", - "cameras = create_pan_cameras(size, device)\n", - "for i, latent in enumerate(latents):\n", - " images = decode_latent_images(xm, latent, cameras, rendering_mode=render_mode)\n", - " display(gif_widget(images))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "85a4dce4", - "metadata": {}, - "outputs": [], - "source": [ - "# Example of saving the latents as meshes.\n", - "from shap_e.util.notebooks import decode_latent_mesh\n", - "\n", - "for i, latent in enumerate(latents):\n", - " t = decode_latent_mesh(xm, latent).tri_mesh()\n", - " with open(f'example_mesh_{i}.ply', 'wb') as f:\n", - " t.write_ply(f)\n", - " with open(f'example_mesh_{i}.obj', 'w') as f:\n", - " t.write_obj(f)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} + "cells": [ + { + "cell_type": "code", + "source": [ + "!pip install torch\n", + "!pip install git+https://github.com/openai/shap-e.git" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "JJQn3gf0xDeB", + "outputId": "9e9ad838-dd0e-4ef7-d03b-b24c790c0a8f" + }, + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", + "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.0.0+cu118)\n", + "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.1)\n", + "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch) (4.5.0)\n", + "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.2)\n", + "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch) (1.11.1)\n", + "Requirement already satisfied: 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/tmp/pip-ephem-wheel-cache-rmf1llx4/wheels/da/2b/4c/d6691fa9597aac8bb85d2ac13b112deb897d5b50f5ad9a37e4\n", + " Building wheel for fire (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + " Created wheel for fire: filename=fire-0.5.0-py2.py3-none-any.whl size=116952 sha256=152e80387b11e5143e4358c4dd198aa71fb87cb44e18b92d79901a366bdb45ec\n", + " Stored in directory: /root/.cache/pip/wheels/90/d4/f7/9404e5db0116bd4d43e5666eaa3e70ab53723e1e3ea40c9a95\n", + "Successfully built shap-e clip fire\n", + "Installing collected packages: pycryptodomex, ftfy, fire, blobfile, clip, shap-e\n", + "Successfully installed blobfile-2.0.2 clip-1.0 fire-0.5.0 ftfy-6.1.1 pycryptodomex-3.17 shap-e-0.0.0\n" + ] + } + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "LE3w48m3vtjs" + }, + "outputs": [], + "source": [ + "import torch\n", + "\n", + "from shap_e.diffusion.sample import sample_latents\n", + "from shap_e.diffusion.gaussian_diffusion import diffusion_from_config\n", + "from shap_e.models.download import load_model, load_config\n", + "from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget" + ] + }, + { + "cell_type": "code", + "source": [ + "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')" + ], + "metadata": { + "id": "bNeX9fKExUv1" + }, + "execution_count": 3, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "xm = load_model('transmitter', device=device)\n", + "model = load_model('text300M', device=device)\n", + "diffusion = diffusion_from_config(load_config('diffusion'))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 99, + "referenced_widgets": [ + "d512d0ab723440d783044a4d7b8017f2", + "e5448c61c0e84de2a82a67f7bef140e3", + "37cc896646f64d87901c3d5d26d1e567", + "0e76e9b71956408aaeaf416482db88f7", + "2205056eb60f4ab8a0e9582bdd95f1eb", + "076e13ee6af54e3c8c9147bd346e07db", + "055b71222e734721adc91399fe4cb833", + 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shap_e/examples/.idea/modules.xml | 8 + shap_e/examples/.idea/vcs.xml | 6 + shap_e/examples/sample_text_to_3d.ipynb | 3577 +++++++++-------- ...).ipynb => sample_text_to_3d_gradio.ipynb} | 0 7 files changed, 1836 insertions(+), 1778 deletions(-) create mode 100644 shap_e/examples/.idea/.gitignore create mode 100644 shap_e/examples/.idea/examples.iml create mode 100644 shap_e/examples/.idea/misc.xml create mode 100644 shap_e/examples/.idea/modules.xml create mode 100644 shap_e/examples/.idea/vcs.xml rename shap_e/examples/{sample_text_to_3d(Gradio_UI).ipynb => sample_text_to_3d_gradio.ipynb} (100%) diff --git a/shap_e/examples/.idea/.gitignore b/shap_e/examples/.idea/.gitignore new file mode 100644 index 00000000..13566b81 --- /dev/null +++ b/shap_e/examples/.idea/.gitignore @@ -0,0 +1,8 @@ +# Default ignored files +/shelf/ +/workspace.xml +# Editor-based HTTP Client requests +/httpRequests/ +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml diff --git 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ftfy-6.1.1 pycryptodomex-3.17 shap-e-0.0.0\n" + ] } + ] }, - "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "LE3w48m3vtjs", + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import torch\n", + "\n", + "from shap_e.diffusion.sample import sample_latents\n", + "from shap_e.diffusion.gaussian_diffusion import diffusion_from_config\n", + "from shap_e.models.download import load_model, load_config\n", + "from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget" + ] + }, + { + "cell_type": "code", + "source": [ + "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')" + ], + "metadata": { + "id": "bNeX9fKExUv1", + "pycharm": { + "name": "#%%\n" + } + }, + "execution_count": 3, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "xm = load_model('transmitter', device=device)\n", + "model = load_model('text300M', device=device)\n", + "diffusion = diffusion_from_config(load_config('diffusion'))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 99, + "referenced_widgets": [ + "d512d0ab723440d783044a4d7b8017f2", + "e5448c61c0e84de2a82a67f7bef140e3", + "37cc896646f64d87901c3d5d26d1e567", + "0e76e9b71956408aaeaf416482db88f7", + "2205056eb60f4ab8a0e9582bdd95f1eb", + "076e13ee6af54e3c8c9147bd346e07db", + "055b71222e734721adc91399fe4cb833", + "965a79f0222142999effdffccdaac314", + "5a718dc2748f4ac6852d27d66f47ffa8", + "4c3bcc6ed2b64169a216896cc168678d", + "b1c1f823f23d42fc85acbacbc87fed02", + "063d545555944639a15723b9f91478db", + "4f72c0bc8ffc4bfea732bded7987742b", + "904211d72c3e4905a1d9f2767e6ce06e", + "9b36554f71aa4094b23cbec75b2785cd", + "ff23844065e64305b70b8c53469452ea", + "33d5b6ce980742d189f7d8abd7275dbd", + "7b1ccadce8844eccbd9cf8f7e455dce5", + "eefc7706774646a5bbb607734e1e4e53", + "db35b5b2aa6844b9910746a6634033e4", + "c8d25e7efa074c729e742404fa8e331c", + "bbc98557389244edaeb392a9d16f65cb" 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"stream", + "name": "stderr", + "text": [ + "100%|███████████████████████████████████████| 890M/890M [00:11<00:00, 81.3MiB/s]\n" + ] }, { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "id": "LE3w48m3vtjs" - }, - "outputs": [], - "source": [ - "import torch\n", - "\n", - "from shap_e.diffusion.sample import sample_latents\n", - "from shap_e.diffusion.gaussian_diffusion import diffusion_from_config\n", - "from shap_e.models.download import load_model, load_config\n", - "from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget" - ] + "output_type": "display_data", + "data": { + "text/plain": [ + " 0%| | 0.00/1.26G [00:00 Date: Wed, 10 May 2023 15:04:11 +0600 Subject: [PATCH 3/4] fixed filename & added both pip install commands Added pip install both for git clone and directly pip install method --- README.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index f2ba2af2..90b20a9e 100644 --- a/README.md +++ b/README.md @@ -63,11 +63,14 @@ Here are some highlighted samples from our text-conditional model. For random sa # Usage - +clone the repository git clone `https://github.com/openai/shap-e.git` Install with `pip install -e .`. +Alternative method: `pip install git+https://github.com/openai/shap-e.git` + To get started with examples, see the following notebooks: -* [sample_text_to_3d.ipynb](shap_e/examples/sample_text_to_3d.ipynb) - sample a 3D model, conditioned on a text prompt +* [sample_text_to_3d.ipynb](shap_e/examples/sample_text_to_3d.ipynb) - sample a 3D model, conditioned on a text promp*t +* [sample_text_to_3d_gradio.ipynb](shap_e/examples/sample_text_to_3d_gradio.ipynb) - sample a 3D model, wrapped around Gradio UI * [sample_image_to_3d.ipynb](shap_e/examples/sample_image_to_3d.ipynb) - sample a 3D model, conditioned on an synthetic view image. * [encode_model.ipynb](shap_e/examples/encode_model.ipynb) - loads a 3D model or a trimesh, creates a batch of multiview renders and a point cloud, encodes them into a latent, and renders it back. For this to work, install Blender version 3.3.1 or higher, and set the environment variable `BLENDER_PATH` to the path of the Blender executable. From db633b273c70523387652f7d02d9a061f6b4c4c8 Mon Sep 17 00:00:00 2001 From: TAWSIF AHMED Date: Wed, 10 May 2023 19:44:05 +0600 Subject: [PATCH 4/4] added huggingface badge --- README.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/README.md b/README.md index 90b20a9e..d3500da6 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,7 @@ +### Huggingface Live Demo +[![Hugging Face Models](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Models-orange)](https://huggingface.co/spaces/hysts/Shap-E) + + # Shap-E This is the official code and model release for [Shap-E: Generating Conditional 3D Implicit Functions](https://arxiv.org/abs/2305.02463).