Implement new renderers and utilitary methods

.gitattributes

@@ -0,0 +1 @@
+*.h5 filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,11 @@
+.vscode/settings.json
+__pycache__/*
+output/*
+input/*
+baselMorphableModel/*
+faceNext/*
+drjit/*
+mitsuba/*
+*.pyc
+ext/*
+chi2_data.py

INSTALL

@@ -5,4 +5,5 @@ pip install redner-gpu
 conda install -c conda-forge opencv
 conda install -c 1adrianb face_alignment=1.2.0
 conda install -c anaconda h5py
-pip install mediapipe
+pip install mediapipe
+pip install mitsuba

commands_demo.ipynb

@@ -0,0 +1,178 @@
+{
+  "cells": [
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Generate"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Reconstruction of a face from a single image ( Vertex / Redner / Mitsuba)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "! py -u ./optimizer.py --input input/test/s1.png --output output/test/mitsuba_blank_text"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Batch reconstruction of a faces from a folder ( Vertex / Redner)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "! py ./optimizer.py --input input/test/ --output output/test/all_images/vertex_reg "
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Batch reconstruction of faces in loop (Mitsuba)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "py ./optimizer.py --input input/test/s1.png --output output/test/mitsuba_rednermat_clip\n"
+          ]
+        }
+      ],
+      "source": [
+        "import os\n",
+        "import subprocess\n",
+        "# Directory path containing all images\n",
+        "imageFolderPath = './input/test/'\n",
+        "\n",
+        "outputDir = './output/test/mitsuba_rednermat_clip'\n",
+        "#setup\n",
+        "if not os.path.exists(outputDir):\n",
+        "    os.makedirs(outputDir)  # Create the output directory if it doesn't exist\n",
+        "# Get the names of all files in the specified directory\n",
+        "image_names = [f for f in os.listdir(imageFolderPath) if os.path.isfile(os.path.join(imageFolderPath, f))]\n",
+        "\n",
+        "# Filter only image files by extensions (if required)\n",
+        "image_paths = [os.path.join(imageFolderPath, image_name) for image_name in image_names if image_name.endswith(('.png', '.jpg', '.jpeg'))]\n",
+        "\n",
+        "# Print the command for each image\n",
+        "for image_path in image_paths:\n",
+        "    # Removing the './' from the image path\n",
+        "    image_path = image_path.replace('./', '')\n",
+        "    outputDir = outputDir.replace('./', '')\n",
+        "    command = f'py ./optimizer.py --input {image_path} --output {outputDir}'\n",
+        "    print(command)\n",
+        "    # Execute the command using os.system(command) if desired\n",
+        "    # os.system(command)\n",
+        "    result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)\n",
+        "    print(result.stdout.decode())\n",
+        "    "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "^C\n"
+          ]
+        }
+      ],
+      "source": [
+        "! py ./optimizer.py --input input/test/s3.png --output output/test/mitsuba_rednermat_clip"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Display images"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from PIL import Image\n",
+        "import matplotlib.pyplot as plt\n",
+        "def display_images_in_folder(folder_path):\n",
+        "    # Iterate through the folder and subfolders\n",
+        "    for root, dirs, files in os.walk(folder_path):\n",
+        "        # Look for the file \"render0.png\" in the current directory\n",
+        "        if \"render_0.png\" in files:\n",
+        "            image_path = os.path.join(root, \"render_0.png\")\n",
+        "            # Open the image using PIL\n",
+        "            image = Image.open(image_path)\n",
+        "            # Display the image\n",
+        "            # Plot and display the image using Matplotlib\n",
+        "            plt.imshow(image)\n",
+        "            plt.axis('off')  # Turn off axis\n",
+        "            plt.title(f\"Image from: {root}\")\n",
+        "            plt.show()\n",
+        "\n",
+        "# Path to the output directory\n",
+        "output_folder_path = outputDir\n",
+        "\n",
+        "# Call the function to find and display the images\n",
+        "display_images_in_folder(output_folder_path)\n"
+      ]
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "name": "demo.ipynb",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "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": "3.9.13"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

config.py

@@ -12,7 +12,7 @@ def __init__(self):
 
 		#morphable model
 		self.path = 'baselMorphableModel'
-		self.textureResolution = 256 #256 or 512
+		self.textureResolution = 512 #256 or 512
 		self.trimPca = False  # if True keep only a subset of the pca basis (eigen vectors)
 
 		#spherical harmonics
@@ -51,11 +51,16 @@ def __init__(self):
 		self.weightRoughnessSmoothnessReg = 0.002  # smoothness regularizer weight for roughness texture (at step 3)
 
 		self.debugFrequency = 10 #display frequency during optimization
+		self.debugOutput = False # generate outputs at each debugFrequency 
 		self.saveIntermediateStage = False #if True the output of stage 1 and 2 are saved. stage 3 is always saved which is the output of the optim
+		self.saveTime = False # if True will save the time taken in the txt
 		self.verbose = False #display loss on terminal if true
 
 		self.rtSamples = 500 #the number of ray tracer samples to render the final output
 		self.rtTrainingSamples = 8  # number of ray tracing to use during training
+		self.bounces = 2 # number of bounces
+		self.smoothing = True #should we smooth the face when doing diff
+		self.rendererName = 'redner' #default renderer name
 	def fillFromDicFile(self, filePath):
 		'''
 		overwrite default config