adding inference notebook

Author: CCareaga

intrinsic_inference.ipynb

@@ -0,0 +1,131 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "gpuType": "T4"
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU"
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "_cPkUxN-ikld"
+      },
+      "outputs": [],
+      "source": [
+        "# install the intrinsic decomposition repo from github\n",
+        "!pip install https://github.com/compphoto/Intrinsic/archive/main.zip"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import torch\n",
+        "\n",
+        "# import some helper functions from chrislib (will be installed by the intrinsic repo)\n",
+        "from chrislib.general import show, view, uninvert\n",
+        "from chrislib.data_util import load_image\n",
+        "\n",
+        "# import model loading and running the pipeline\n",
+        "from intrinsic.pipeline import run_pipeline\n",
+        "from intrinsic.model_util import load_models"
+      ],
+      "metadata": {
+        "id": "J0gn82ZSjomn"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# download the pretrained weights and return the model (may take a bit to download weights)\n",
+        "intrinsic_model = load_models('paper_weights')"
+      ],
+      "metadata": {
+        "id": "Ap3HubpwC_KG"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# load an example image from the github repo\n",
+        "torch.hub.download_url_to_file('https://raw.githubusercontent.com/compphoto/Intrinsic/main/figures/avocado.png', 'avo.png')"
+      ],
+      "metadata": {
+        "id": "m_NYfDx0AhTw"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# load the image to run through the pipeline\n",
+        "img = load_image('/content/avo.png')"
+      ],
+      "metadata": {
+        "id": "ALb4Pjfvj-MU"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# run the image through the pipeline (use R0 resizing dicussed in the paper)\n",
+        "result = run_pipeline(\n",
+        "    intrinsic_model,\n",
+        "    img,\n",
+        "    resize_conf=0.0,\n",
+        "    maintain_size=True,\n",
+        "    linear=False,\n",
+        "    device='cuda'\n",
+        ")"
+      ],
+      "metadata": {
+        "id": "QW0TiFypkOj-"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# convert the inverse shading to regular shading for visualization\n",
+        "shd = uninvert(result['inv_shading'])\n",
+        "alb = result['albedo']"
+      ],
+      "metadata": {
+        "id": "XpYY2MNjkp2f"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# show the result (gamma corrects the linear intrinsic components and scales to [0-1])\n",
+        "show([img, view(shd), view(alb)], size=(20, 7))"
+      ],
+      "metadata": {
+        "id": "8KKbyoVLki9s"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}