app code for precomputed

README.md

@@ -1,8 +1,8 @@
 ---
 title: Zero123
-emoji: 📈
+emoji: 👀
 colorFrom: indigo
-colorTo: yellow
+colorTo: purple
 sdk: gradio
 sdk_version: 3.20.1
 app_file: app.py

app.py

@@ -0,0 +1,97 @@
+import numpy as np
+import gradio as gr
+import os
+from PIL import Image
+from functools import partial
+
+def retrieve_input_image(dataset, inputs):
+    img_id = inputs
+    img_path = os.path.join('online_demo', dataset, 'step-100_scale-6.0', img_id, 'input.png')
+    image = Image.open(img_path)
+    return image
+
+def retrieve_novel_view(dataset, img_id, polar, azimuth, zoom, seed):
+    polar = polar // 30 + 1
+    azimuth = azimuth // 30
+    zoom = int(zoom * 2 + 1)
+    img_path = os.path.join('online_demo', dataset, 'step-100_scale-6.0', img_id,\
+                            'polar-%d_azimuth-%d_distance-%d_seed-%d.png' % (polar, azimuth, zoom, seed))
+    image = Image.open(img_path)
+    return image
+    
+
+with gr.Blocks() as demo:
+    gr.Markdown("Flip text or image files using this demo.")
+    with gr.Tab("In-the-wild Images"):
+        with gr.Row():
+            with gr.Column(scale=1):
+                default_input_image = Image.open( os.path.join('online_demo', 'nerf_wild', 'step-100_scale-6.0', 'car1', 'input.png'))
+                input_image = gr.Image(default_input_image, shape=[256, 256])
+                options = sorted(os.listdir('online_demo/nerf_wild/step-100_scale-6.0'))
+                img_id = gr.Dropdown(options, value='car1')
+                text_button = gr.Button("Choose Input Image")
+                retrieve_input_image_dataset = partial(retrieve_input_image, 'nerf_wild')
+                text_button.click(retrieve_input_image_dataset, inputs=img_id, outputs=input_image)
+
+            with gr.Column(scale=1):
+                novel_view = gr.Image(shape=[256, 256])
+                inputs = [img_id,
+                gr.Slider(-30, 30, value=0, step=30, label='Polar angle (vertical rotation in degrees)'),
+                gr.Slider(0, 330, value=0, step=30, label='Azimuth angle (horizontal rotation in degrees)'),
+                gr.Slider(-0.5, 0.5, value=0, step=0.5, label='Zoom'),
+                gr.Slider(1, 4, value=1, step=1, label='Random seed')]
+                
+                submit_button = gr.Button("Get Novel View")
+                retrieve_novel_view_dataset = partial(retrieve_novel_view, 'nerf_wild')
+                submit_button.click(retrieve_novel_view_dataset, inputs=inputs, outputs=novel_view)
+        
+    with gr.Tab("Google Scanned Objects"):
+        with gr.Row():
+            with gr.Column(scale=1):
+                default_input_image = Image.open( os.path.join('online_demo', 'GSO', 'step-100_scale-6.0', 'SAMBA_HEMP', 'input.png'))
+                input_image = gr.Image(default_input_image, shape=[256, 256])
+                options = sorted(os.listdir('online_demo/GSO/step-100_scale-6.0'))
+                img_id = gr.Dropdown(options, value='SAMBA_HEMP')
+                text_button = gr.Button("Choose Input Image")
+                retrieve_input_image_dataset = partial(retrieve_input_image, 'GSO')
+                text_button.click(retrieve_input_image_dataset, inputs=img_id, outputs=input_image)
+
+            with gr.Column(scale=1):
+                novel_view = gr.Image(shape=[256, 256])
+                inputs = [img_id,
+                gr.Slider(-30, 30, value=0, step=30, label='Polar angle (vertical rotation in degrees)'),
+                gr.Slider(0, 330, value=0, step=30, label='Azimuth angle (horizontal rotation in degrees)'),
+                gr.Slider(-0.5, 0.5, value=0, step=0.5, label='Zoom'),
+                gr.Slider(1, 4, value=1, step=1, label='Random seed')]
+                
+                submit_button = gr.Button("Get Novel View")
+                retrieve_novel_view_dataset = partial(retrieve_novel_view, 'GSO')
+                submit_button.click(retrieve_novel_view_dataset, inputs=inputs, outputs=novel_view)
+        
+    with gr.Tab("RTMV"):
+        with gr.Row():
+            with gr.Column(scale=1):
+                default_input_image = Image.open( os.path.join('online_demo', 'RTMV', 'step-100_scale-6.0', '00000', 'input.png'))
+                input_image = gr.Image(default_input_image, shape=[256, 256])
+                options = sorted(os.listdir('online_demo/RTMV/step-100_scale-6.0'))
+                img_id = gr.Dropdown(options, value='00000')
+                text_button = gr.Button("Choose Input Image")
+                retrieve_input_image_dataset = partial(retrieve_input_image, 'RTMV')
+                text_button.click(retrieve_input_image_dataset, inputs=img_id, outputs=input_image)
+
+            with gr.Column(scale=1):
+                novel_view = gr.Image(shape=[256, 256])
+                inputs = [img_id,
+                gr.Slider(-30, 30, value=0, step=30, label='Polar angle (vertical rotation in degrees)'),
+                gr.Slider(0, 330, value=0, step=30, label='Azimuth angle (horizontal rotation in degrees)'),
+                gr.Slider(-0.5, 0.5, value=0, step=0.5, label='Zoom'),
+                gr.Slider(1, 4, value=1, step=1, label='Random seed')]
+                
+                submit_button = gr.Button("Get Novel View")
+                retrieve_novel_view_dataset = partial(retrieve_novel_view, 'RTMV')
+                submit_button.click(retrieve_novel_view_dataset, inputs=inputs, outputs=novel_view)
+    
+    
+
+if __name__ == "__main__":
+    demo.launch()

run.ipynb

@@ -0,0 +1,187 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": 3.0293430767166755e+38,
+   "metadata": {
+    "id": 3.0293430767166755e+38
+   },
+   "source": [
+    "# Gradio Demo: blocks_flipper"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": 2.8891853944186117e+38,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 616
+    },
+    "id": 2.8891853944186117e+38,
+    "outputId": "b60a6d5e-045d-4b40-bfd8-6caa407a34df",
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Thanks for being a Gradio user! If you have questions or feedback, please join our Discord server and chat with us: https://discord.gg/feTf9x3ZSB\n",
+      "Running on local URL:  http://127.0.0.1:7908\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7908/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import gradio as gr\n",
+    "import os\n",
+    "from PIL import Image\n",
+    "from functools import partial\n",
+    "\n",
+    "def retrieve_input_image(dataset, inputs):\n",
+    "    img_id = inputs\n",
+    "    img_path = os.path.join('online_demo', dataset, 'step-100_scale-6.0', img_id, 'input.png')\n",
+    "    image = Image.open(img_path)\n",
+    "    return image\n",
+    "\n",
+    "def retrieve_novel_view(dataset, img_id, polar, azimuth, zoom, seed):\n",
+    "    polar = polar // 30 + 1\n",
+    "    azimuth = azimuth // 30\n",
+    "    zoom = int(zoom * 2 + 1)\n",
+    "    img_path = os.path.join('online_demo', dataset, 'step-100_scale-6.0', img_id,\\\n",
+    "                            'polar-%d_azimuth-%d_distance-%d_seed-%d.png' % (polar, azimuth, zoom, seed))\n",
+    "    image = Image.open(img_path)\n",
+    "    return image\n",
+    "    \n",
+    "\n",
+    "with gr.Blocks() as demo:\n",
+    "    gr.Markdown(\"Flip text or image files using this demo.\")\n",
+    "    with gr.Tab(\"In-the-wild Images\"):\n",
+    "        with gr.Row():\n",
+    "            with gr.Column(scale=1):\n",
+    "                default_input_image = Image.open( os.path.join('online_demo', 'nerf_wild', 'step-100_scale-6.0', 'car1', 'input.png'))\n",
+    "                input_image = gr.Image(default_input_image, shape=[256, 256])\n",
+    "                options = sorted(os.listdir('online_demo/nerf_wild/step-100_scale-6.0'))\n",
+    "                img_id = gr.Dropdown(options, value='car1')\n",
+    "                text_button = gr.Button(\"Choose Input Image\")\n",
+    "                retrieve_input_image_dataset = partial(retrieve_input_image, 'nerf_wild')\n",
+    "                text_button.click(retrieve_input_image_dataset, inputs=img_id, outputs=input_image)\n",
+    "\n",
+    "            with gr.Column(scale=1):\n",
+    "                novel_view = gr.Image(shape=[256, 256])\n",
+    "                inputs = [img_id,\n",
+    "                gr.Slider(-30, 30, value=0, step=30, label='Polar angle (vertical rotation in degrees)'),\n",
+    "                gr.Slider(0, 330, value=0, step=30, label='Azimuth angle (horizontal rotation in degrees)'),\n",
+    "                gr.Slider(-0.5, 0.5, value=0, step=0.5, label='Zoom'),\n",
+    "                gr.Slider(1, 4, value=1, step=1, label='Random seed')]\n",
+    "                \n",
+    "                submit_button = gr.Button(\"Get Novel View\")\n",
+    "                retrieve_novel_view_dataset = partial(retrieve_novel_view, 'nerf_wild')\n",
+    "                submit_button.click(retrieve_novel_view_dataset, inputs=inputs, outputs=novel_view)\n",
+    "        \n",
+    "    with gr.Tab(\"Google Scanned Objects\"):\n",
+    "        with gr.Row():\n",
+    "            with gr.Column(scale=1):\n",
+    "                default_input_image = Image.open( os.path.join('online_demo', 'GSO', 'step-100_scale-6.0', 'SAMBA_HEMP', 'input.png'))\n",
+    "                input_image = gr.Image(default_input_image, shape=[256, 256])\n",
+    "                options = sorted(os.listdir('online_demo/GSO/step-100_scale-6.0'))\n",
+    "                img_id = gr.Dropdown(options, value='SAMBA_HEMP')\n",
+    "                text_button = gr.Button(\"Choose Input Image\")\n",
+    "                retrieve_input_image_dataset = partial(retrieve_input_image, 'GSO')\n",
+    "                text_button.click(retrieve_input_image_dataset, inputs=img_id, outputs=input_image)\n",
+    "\n",
+    "            with gr.Column(scale=1):\n",
+    "                novel_view = gr.Image(shape=[256, 256])\n",
+    "                inputs = [img_id,\n",
+    "                gr.Slider(-30, 30, value=0, step=30, label='Polar angle (vertical rotation in degrees)'),\n",
+    "                gr.Slider(0, 330, value=0, step=30, label='Azimuth angle (horizontal rotation in degrees)'),\n",
+    "                gr.Slider(-0.5, 0.5, value=0, step=0.5, label='Zoom'),\n",
+    "                gr.Slider(1, 4, value=1, step=1, label='Random seed')]\n",
+    "                \n",
+    "                submit_button = gr.Button(\"Get Novel View\")\n",
+    "                retrieve_novel_view_dataset = partial(retrieve_novel_view, 'GSO')\n",
+    "                submit_button.click(retrieve_novel_view_dataset, inputs=inputs, outputs=novel_view)\n",
+    "        \n",
+    "    with gr.Tab(\"RTMV\"):\n",
+    "        with gr.Row():\n",
+    "            with gr.Column(scale=1):\n",
+    "                default_input_image = Image.open( os.path.join('online_demo', 'RTMV', 'step-100_scale-6.0', '00000', 'input.png'))\n",
+    "                input_image = gr.Image(default_input_image, shape=[256, 256])\n",
+    "                options = sorted(os.listdir('online_demo/RTMV/step-100_scale-6.0'))\n",
+    "                img_id = gr.Dropdown(options, value='00000')\n",
+    "                text_button = gr.Button(\"Choose Input Image\")\n",
+    "                retrieve_input_image_dataset = partial(retrieve_input_image, 'RTMV')\n",
+    "                text_button.click(retrieve_input_image_dataset, inputs=img_id, outputs=input_image)\n",
+    "\n",
+    "            with gr.Column(scale=1):\n",
+    "                novel_view = gr.Image(shape=[256, 256])\n",
+    "                inputs = [img_id,\n",
+    "                gr.Slider(-30, 30, value=0, step=30, label='Polar angle (vertical rotation in degrees)'),\n",
+    "                gr.Slider(0, 330, value=0, step=30, label='Azimuth angle (horizontal rotation in degrees)'),\n",
+    "                gr.Slider(-0.5, 0.5, value=0, step=0.5, label='Zoom'),\n",
+    "                gr.Slider(1, 4, value=1, step=1, label='Random seed')]\n",
+    "                \n",
+    "                submit_button = gr.Button(\"Get Novel View\")\n",
+    "                retrieve_novel_view_dataset = partial(retrieve_novel_view, 'RTMV')\n",
+    "                submit_button.click(retrieve_novel_view_dataset, inputs=inputs, outputs=novel_view)\n",
+    "    \n",
+    "    \n",
+    "\n",
+    "if __name__ == \"__main__\":\n",
+    "    demo.launch()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bk8_q39r_iGt",
+   "metadata": {
+    "id": "bk8_q39r_iGt"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": []
+  },
+  "gpuClass": "standard",
+  "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": "3.9.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}