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94 lines
2.3 KiB
94 lines
2.3 KiB
2 years ago
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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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.models.download import load_model\n",
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"from shap_e.util.data_util import load_or_create_multimodal_batch\n",
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"from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget"
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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": 2,
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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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"metadata": {},
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"outputs": [],
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"source": [
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"xm = load_model('transmitter', device=device)"
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"model_path = \"example_data/cactus/object.obj\"\n",
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"\n",
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"# This may take a few minutes, since it requires rendering the model twice\n",
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"# in two different modes.\n",
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"batch = load_or_create_multimodal_batch(\n",
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" device,\n",
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" model_path=model_path,\n",
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" mv_light_mode=\"basic\",\n",
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" mv_image_size=256,\n",
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" cache_dir=\"example_data/cactus/cached\",\n",
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" verbose=True, # this will show Blender output during renders\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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"metadata": {},
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"outputs": [],
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"source": [
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"with torch.no_grad():\n",
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" latent = xm.encoder.encode_to_bottleneck(batch)\n",
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"\n",
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" render_mode = 'stf' # you can change this to 'nerf'\n",
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" size = 128 # recommended that you lower resolution when using nerf\n",
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"\n",
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" cameras = create_pan_cameras(size, device)\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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