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108 lines
2.7 KiB
108 lines
2.7 KiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "964ccced",
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"metadata": {},
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"outputs": [],
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"source": [
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"import torch\n",
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"\n",
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"from shap_e.diffusion.sample import sample_latents\n",
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"from shap_e.diffusion.gaussian_diffusion import diffusion_from_config\n",
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"from shap_e.models.download import load_model, load_config\n",
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"from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget\n",
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"from shap_e.util.image_util import load_image"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8eed3a76",
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"metadata": {},
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"outputs": [],
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"source": [
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"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2d922637",
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"metadata": {},
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"outputs": [],
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"source": [
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"xm = load_model('transmitter', device=device)\n",
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"model = load_model('image300M', device=device)\n",
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"diffusion = diffusion_from_config(load_config('diffusion'))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "53d329d0",
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"metadata": {},
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"outputs": [],
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"source": [
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"batch_size = 4\n",
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"guidance_scale = 3.0\n",
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"\n",
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"image = load_image(\"example_data/corgi.png\")\n",
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"\n",
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"latents = sample_latents(\n",
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" batch_size=batch_size,\n",
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" model=model,\n",
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" diffusion=diffusion,\n",
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" guidance_scale=guidance_scale,\n",
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" model_kwargs=dict(images=[image] * batch_size),\n",
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" progress=True,\n",
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" clip_denoised=True,\n",
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" use_fp16=True,\n",
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" use_karras=True,\n",
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" karras_steps=64,\n",
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" sigma_min=1e-3,\n",
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" sigma_max=160,\n",
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" s_churn=0,\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "633da2ec",
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"metadata": {},
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"outputs": [],
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"source": [
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"render_mode = 'nerf' # you can change this to 'stf' for mesh rendering\n",
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"size = 64 # this is the size of the renders; higher values take longer to render.\n",
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"\n",
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"cameras = create_pan_cameras(size, device)\n",
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"for i, latent in enumerate(latents):\n",
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" images = decode_latent_images(xm, latent, cameras, rendering_mode=render_mode)\n",
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" display(gif_widget(images))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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