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diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..cc3e305834f64a1e15b3cd83c9cdc653dc5647a4
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+---
+language:
+- en
+size_categories:
+- 1K<n<10K
+task_categories:
+- image-to-image
+- unconditional-image-generation
+- image-classification
+- text-to-image
+pretty_name: MatSynth
+dataset_info:
+  features:
+  - name: name
+    dtype: string
+  - name: category
+    dtype:
+      class_label:
+        names:
+          '0': ceramic
+          '1': concrete
+          '2': fabric
+          '3': ground
+          '4': leather
+          '5': marble
+          '6': metal
+          '7': misc
+          '8': plaster
+          '9': plastic
+          '10': stone
+          '11': terracotta
+          '12': wood
+  - name: metadata
+    struct:
+    - name: authors
+      sequence: string
+    - name: category
+      dtype: string
+    - name: description
+      dtype: string
+    - name: height_factor
+      dtype: float32
+    - name: height_mean
+      dtype: float32
+    - name: license
+      dtype: string
+    - name: link
+      dtype: string
+    - name: maps
+      sequence: string
+    - name: method
+      dtype: string
+    - name: name
+      dtype: string
+    - name: physical_size
+      dtype: float32
+    - name: source
+      dtype: string
+    - name: stationary
+      dtype: bool
+    - name: tags
+      sequence: string
+    - name: version_date
+      dtype: string
+  - name: basecolor
+    dtype: image
+  - name: diffuse
+    dtype: image
+  - name: displacement
+    dtype: image
+  - name: height
+    dtype: image
+  - name: metallic
+    dtype: image
+  - name: normal
+    dtype: image
+  - name: opacity
+    dtype: image
+  - name: roughness
+    dtype: image
+  - name: specular
+    dtype: image
+  - name: blend_mask
+    dtype: image
+  splits:
+  - name: test
+    num_bytes: 7443356066.0
+    num_examples: 89
+  - name: train
+    num_bytes: 430581667965.1
+    num_examples: 5700
+  download_size: 440284274332
+  dataset_size: 438025024031.1
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path: data/test-*
+  - split: train
+    path: data/train-*
+tags:
+- materials
+- pbr
+- 4d
+- graphics
+- rendering
+- svbrdf
+- synthetic
+viewer: false
+---
+
+# MatSynth
+
+MatSynth is a Physically Based Rendering (PBR) materials dataset designed for modern AI applications.
+This dataset consists of over 4,000 ultra-high resolution, offering unparalleled scale, diversity, and detail. 
+
+Meticulously collected and curated, MatSynth is poised to drive innovation in material acquisition and generation applications, providing a rich resource for researchers, developers, and enthusiasts in computer graphics and related fields.
+
+For further information, refer to our paper: ["MatSynth: A Modern PBR Materials Dataset"](https://arxiv.org/abs/2401.06056) available on arXiv.
+
+<center>
+  <img src="https://gvecchio.com/matsynth/static/images/teaser.png" style="border-radius:10px">
+</center>
+
+## 🔍 Dataset Details
+
+### Dataset Description
+
+MatSynth is a new large-scale dataset comprising over 4,000 ultra-high resolution Physically Based Rendering (PBR) materials, 
+all released under permissive licensing.
+
+All materials in the dataset are represented by a common set of maps (*Basecolor*, *Diffuse*, *Normal*, *Height*, *Roughness*, *Metallic*, *Specular* and, when useful, *Opacity*), 
+modelling both the reflectance and mesostructure of the material.
+
+Each material in the dataset comes with rich metadata, including information on its origin, licensing details, category, tags, creation method, 
+and, when available, descriptions and physical size. 
+This comprehensive metadata facilitates precise material selection and usage, catering to the specific needs of users.
+
+<center>
+  <img src="https://gvecchio.com/matsynth/static/images/data.png" style="border-radius:10px">
+</center>
+
+## 📂 Dataset Structure
+ 
+The MatSynth dataset is divided into two splits: the test split, containing 89 materials, and the train split, consisting of 3,980 materials. 
+
+## 🔨 Dataset Creation
+
+The MatSynth dataset is designed to support modern, learning-based techniques for a variety of material-related tasks including, 
+but not limited to, material acquisition, material generation and synthetic data generation e.g. for retrieval or segmentation. 
+
+### 🗃️ Source Data
+
+The MatSynth dataset is the result of an extensively collection of data from multiple online sources operating under the CC0 and CC-BY licensing framework. 
+This collection strategy allows to capture a broad spectrum of materials, 
+from commonly used ones to more niche or specialized variants while guaranteeing that the data can be used for a variety of usecases. 
+
+Materials under CC0 license were collected from [AmbientCG](https://ambientcg.com/), [CGBookCase](https://www.cgbookcase.com/), [PolyHeaven](https://polyhaven.com/), 
+[ShateTexture](https://www.sharetextures.com/), and [TextureCan](https://www.texturecan.com/).
+The dataset also includes limited set of materials from the artist [Julio Sillet](https://juliosillet.gumroad.com/), distributed under CC-BY license.
+
+We collected over 6000 materials which we meticulously filter to keep only tileable, 4K materials. 
+This high resolution allows us to extract many different crops from each sample at different scale for augmentation. 
+Additionally, we discard blurry or low-quality materials (by visual inspection). 
+The resulting dataset consists of 3736 unique materials which we augment by blending semantically compatible materials (e.g.: snow over ground). 
+In total, our dataset contains 4069 unique 4K materials.
+
+### ✒️ Annotations
+
+The dataset is composed of material maps (Basecolor, Diffuse, Normal, Height, Roughness, Metallic, Specular and, when useful, opacity) 
+and associated renderings under varying environmental illuminations, and multi-scale crops.
+We adopt the OpenGL standard for the Normal map (Y-axis pointing upward). 
+The Height map is given in a 16-bit single channel format for higher precision.
+
+In addition to these maps, the dataset includes other annotations providing context to each material: 
+the capture method (photogrammetry, procedural generation, or approximation); 
+list of descriptive tags; source name (website); source link; 
+licensing and a timestamps for eventual future versioning. 
+For a subset of materials, when the information is available, we also provide the author name (387), text description (572) and a physical size, 
+presented as the length of the edge in centimeters (358). 
+
+## 🧑‍💻 Usage
+
+MatSynth is accessible through the datasets python library.
+Following a usage example:
+
+```python
+import torchvision.transforms.functional as TF
+from datasets import load_dataset
+from torch.utils.data import DataLoader
+
+# image processing function
+def process_img(x):
+    x = TF.resize(x, (1024, 1024))
+    x = TF.to_tensor(x)
+    return x
+
+# item processing function
+def process_batch(examples):
+    examples["basecolor"] = [process_img(x) for x in examples["basecolor"]]
+    return examples
+
+# load the dataset in streaming mode
+ds = load_dataset(
+    "gvecchio/MatSynth", 
+    streaming = True,
+)
+
+# remove unwanted columns
+ds = ds.remove_columns(["diffuse", "specular", "displacement", "opacity", "blend_mask"])
+# or keep only specified columns
+ds = ds.select_columns(["metadata", "basecolor"])
+
+# shuffle data
+ds = ds.shuffle(buffer_size=100)
+
+# filter data matching a specific criteria, e.g.: only CC0 materials
+ds = ds.filter(lambda x: x["metadata"]["license"] == "CC0")
+# filter out data from Deschaintre et al. 2018
+ds = ds.filter(lambda x: x["metadata"]["source"] != "deschaintre_2020")
+
+# Set up processing
+ds = ds.map(process_batch, batched=True, batch_size=8)
+
+# set format for usage in torch
+ds = ds.with_format("torch")
+
+# iterate over the dataset
+for x in ds:
+    print(x)
+
+```
+
+ ⚠️ **Note**: Streaming can be slow. We strongly suggest to cache data locally. 
+
+## 📜 Citation
+
+```
+@inproceedings{vecchio2023matsynth,
+  title={MatSynth: A Modern PBR Materials Dataset},
+  author={Vecchio, Giuseppe and Deschaintre, Valentin},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+  year={2024}
+}
+```
+
+If you use the data from Deschaintre et al. contained in this dataset, please also cite: 
+```
+@article{deschaintre2018single,
+  title={Single-image svbrdf capture with a rendering-aware deep network},
+  author={Deschaintre, Valentin and Aittala, Miika and Durand, Fredo and Drettakis, George and Bousseau, Adrien},
+  journal={ACM Transactions on Graphics (ToG)},
+  volume={37},
+  number={4},
+  pages={1--15},
+  year={2018},
+  publisher={ACM New York, NY, USA}
+}
+```
\ No newline at end of file
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diff --git a/scripts/assemble_render.py b/scripts/assemble_render.py
new file mode 100644
index 0000000000000000000000000000000000000000..9acd96153271e19f0c10d2f9d54e0ad9ed1b4ac0
--- /dev/null
+++ b/scripts/assemble_render.py
@@ -0,0 +1,37 @@
+import argparse
+from pathlib import Path
+
+import torchvision.transforms.functional as TF
+from PIL import Image
+from tqdm import tqdm
+
+if __name__ == "__main__":
+    # Create argument parser
+    parser = argparse.ArgumentParser(description="Assemble renders.")
+    parser.add_argument("--source_dir", required=True, help="Directory where the dataset is stored.")
+    args = parser.parse_args()
+
+    source_dir = Path(args.source_dir)
+
+    # Find all materials
+    for render_dir in tqdm([x for x in source_dir.glob("**/renders/")]):
+        passes_dir = render_dir/"passes"
+        num_renders = len(list(passes_dir.glob("*diffuse.png")))
+        
+        for i in range(num_renders):
+            diff_path = passes_dir/f"render_{i:02d}_diffuse.png"
+            glossy_path = passes_dir/f"render_{i:02d}_glossy.png"
+
+            full_path = render_dir/f"render_{i:02d}.png"
+
+            diffuse = TF.to_tensor(Image.open(diff_path))
+            glossy = TF.to_tensor(Image.open(glossy_path))
+
+            diffuse = TF.adjust_gamma(diffuse, 2.2)
+            glossy = TF.adjust_gamma(glossy, 2.2)
+
+            render = diffuse + glossy
+
+            render = TF.adjust_gamma(render, 1/2.2)
+            render = TF.to_pil_image(render)
+            render.save(full_path)
\ No newline at end of file
diff --git a/scripts/download_dataset.py b/scripts/download_dataset.py
new file mode 100644
index 0000000000000000000000000000000000000000..fadf779f671973936205710c9ab079441f18dd0d
--- /dev/null
+++ b/scripts/download_dataset.py
@@ -0,0 +1,53 @@
+from datasets import load_dataset
+import argparse
+from pathlib import Path
+import json
+
+
+def process_batch(examples):
+    return examples
+
+
+if __name__ == "__main__":
+    # Create argument parser
+    parser = argparse.ArgumentParser(description="Download dataset.")
+    parser.add_argument("--base_dir", required=True, help="Directory to save the downloaded files.")
+    args = parser.parse_args()
+
+    base_dir = Path(args.base_dir)
+    base_dir.mkdir(exist_ok=True, parents=True)
+
+    # Load dataset
+    ds = load_dataset(
+        "gvecchio/MatSynth",
+        streaming=True,
+    )
+
+    # Setup dummy processing
+    ds = ds.map(process_batch, batched=False, batch_size=1)
+
+    for split in ds:
+        for item in ds[split]:
+            name = item["name"]
+            dest_dir = base_dir / split / item["metadata"]["category"] / name
+            dest_dir.mkdir(exist_ok=True, parents=True)
+
+            # Save metadata
+            with open(dest_dir / "metadata.json", "w") as f:
+                item["metadata"]["physical_size"] = str(
+                    item["metadata"]["physical_size"]
+                )
+                json.dump(item["metadata"], f, indent=4)
+
+            # Save images
+            item["basecolor"].save(dest_dir / "basecolor.png")
+            item["diffuse"].save(dest_dir / "diffuse.png")
+            item["displacement"].save(dest_dir / "displacement.png")
+            item["specular"].save(dest_dir / "specular.png")
+            item["height"].save(dest_dir / "height.png")
+            item["metallic"].save(dest_dir / "metallic.png")
+            item["normal"].save(dest_dir / "normal.png")
+            item["opacity"].save(dest_dir / "opacity.png")
+            item["roughness"].save(dest_dir / "roughness.png")
+            if item["blend_mask"] is not None:
+                item["blend_mask"].save(dest_dir / "blend_mask.png")
diff --git a/scripts/hdri/DayEnvironmentHDRI015_8K-HDR.exr b/scripts/hdri/DayEnvironmentHDRI015_8K-HDR.exr
new file mode 100644
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--- /dev/null
+++ b/scripts/hdri/DayEnvironmentHDRI015_8K-HDR.exr
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 137129895
diff --git a/scripts/hdri/DaySkyHDRI037B_8K-HDR.exr b/scripts/hdri/DaySkyHDRI037B_8K-HDR.exr
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,3 @@
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diff --git a/scripts/hdri/IndoorEnvironmentHDRI003_8K-HDR.exr b/scripts/hdri/IndoorEnvironmentHDRI003_8K-HDR.exr
new file mode 100644
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--- /dev/null
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diff --git a/scripts/hdri/IndoorEnvironmentHDRI005_8K-HDR.exr b/scripts/hdri/IndoorEnvironmentHDRI005_8K-HDR.exr
new file mode 100644
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--- /dev/null
+++ b/scripts/hdri/IndoorEnvironmentHDRI005_8K-HDR.exr
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 110454310
diff --git a/scripts/hdri/studio_small_02_4k.exr b/scripts/hdri/studio_small_02_4k.exr
new file mode 100644
index 0000000000000000000000000000000000000000..066ee7eaaf693ef11100e4a1dd32ae325bd56aae
--- /dev/null
+++ b/scripts/hdri/studio_small_02_4k.exr
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/scripts/make_crops.py b/scripts/make_crops.py
new file mode 100644
index 0000000000000000000000000000000000000000..9ec86d75020eb0153a7a213b36efa0eb17fd932a
--- /dev/null
+++ b/scripts/make_crops.py
@@ -0,0 +1,107 @@
+import argparse
+import math
+import threading
+from pathlib import Path
+
+import numpy as np
+import torch
+import torchvision.transforms.functional as TF
+from PIL import Image
+from tqdm import tqdm
+
+
+def rotate_normal_map(normal_map, angle_deg):
+    angle_rad = angle_deg * (torch.pi / 180.0)
+
+    normal_map  = normal_map * 2.0 - 1.0 # Convert to [-1, 1]
+    normal_map = normal_map.unsqueeze(0) # Add batch dimension
+
+    # Rotate the Vectors
+    rotation_matrix = torch.tensor([[math.cos(angle_rad), -math.sin(angle_rad), 0],
+                                    [math.sin(angle_rad), math.cos(angle_rad), 0],
+                                    [0, 0, 1]], device=normal_map.device)
+
+    # Reshape for batch matrix multiplication
+    reshaped_normal_map = normal_map.view(1, 3, -1)  # Reshape to [1, 3, H*W]
+    rotation_matrix = rotation_matrix.view(1, 3, 3)  # Add batch dimension
+
+    # Rotate the vectors
+    rotated_vectors = torch.bmm(rotation_matrix, reshaped_normal_map)
+    rotated_vectors = rotated_vectors.view(1, 3, normal_map.size(2), normal_map.size(3))
+
+    rotated_vectors = rotated_vectors / 2.0 + 0.5 # Convert back to [0, 1]
+
+    return rotated_vectors[0]
+
+def process_map(map, mat_dest):
+    map_name = map.stem
+    img = Image.open(map)
+    img = TF.to_tensor(img).cuda()
+    img = TF.resize(img, (4096, 4096), antialias=True)
+
+    img = img.repeat(1, 3, 3)
+    img = TF.center_crop(img, (5793, 5793))
+
+    for rot_angle in range(0, 360, 45):
+        crop_i = 0
+
+        if "normal" in map_name:
+            rot_img = rotate_normal_map(img, axis='z', angle_deg=rot_angle)
+            rot_img = TF.rotate(rot_img, rot_angle)
+        else:
+            rot_img = TF.rotate(img, rot_angle)
+
+        rot_img = TF.center_crop(rot_img, (4096, 4096))
+        
+        for crop_res in [4096, 2048, 1024]:
+            # split into crops
+            crops = rot_img.unfold(1, crop_res, crop_res).unfold(2, crop_res, crop_res)
+            crops = crops.permute(1, 2, 0, 3, 4)
+            crops = crops.reshape(-1, crops.size(2), crop_res, crop_res)
+
+            for crop in crops:
+                crop_dir = mat_dest / f"rot_{rot_angle:03d}_crop_{crop_i:03d}"
+                crop_dir.mkdir(parents=True, exist_ok=True)
+
+                crop = TF.resize(crop, (1024, 1024), antialias=True)
+                
+                if map_name in ["height", "displacement"]:
+                    crop = crop.permute(1, 2, 0).cpu().numpy()
+                    crop = crop.astype(np.uint16)
+                    crop = Image.fromarray(crop[..., 0])
+                    crop.save(crop_dir / f"{map_name}.png")
+                else:
+                    TF.to_pil_image(crop).save(crop_dir / f"{map_name}.png")
+
+                crop_i += 1
+
+if __name__ == "__main__":
+    # Create argument parser
+    parser = argparse.ArgumentParser(description="Make dataset crops.")
+    parser.add_argument("--source_dir", required=True, help="Directory where the original 4K maps are stored.")
+    parser.add_argument("--dest_dir", required=True , help="Destination directory to store the 1K crops.")
+    args = parser.parse_args()
+
+    source_dir = Path(args.source_dir)
+    dest_dir = Path(args.dest_dir)
+
+    # Find all materials in the source directory
+    for file in tqdm([x for x in source_dir.glob("**/basecolor.png")]):
+        mat_dir = file.parent
+
+        name = mat_dir.stem
+        category = mat_dir.parent.stem
+        split = mat_dir.parent.parent.stem
+
+        mat_dest = dest_dir / split / category / name
+        mat_dest.mkdir(parents=True, exist_ok=True)
+
+        thread = []
+        for map in mat_dir.glob("*.png"):
+            t = threading.Thread(target=process_map, args=(map, mat_dest))
+            t.start()
+
+            thread.append(t)
+
+        for t in thread:
+            t.join()
\ No newline at end of file
diff --git a/scripts/render_ambient.blend b/scripts/render_ambient.blend
new file mode 100644
index 0000000000000000000000000000000000000000..8c43965be8cd27b78d5d3d11217de87041b752d9
--- /dev/null
+++ b/scripts/render_ambient.blend
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:09fce0c9a535c86bfa812378c74f826bae8eaa1077a0629b4b878fc1eae2f6ca
+size 1231560
diff --git a/scripts/render_ambient.py b/scripts/render_ambient.py
new file mode 100644
index 0000000000000000000000000000000000000000..8e27df445203e45ebeda7e341a3f3081d1ea0e45
--- /dev/null
+++ b/scripts/render_ambient.py
@@ -0,0 +1,117 @@
+import math
+import random
+import sys
+from pathlib import Path
+
+import bpy
+
+argv = sys.argv
+argv = argv[argv.index("--") + 1:]  # get all args after "--"
+dset_dir = Path(argv[0])
+
+def create_node_once(nodes, name, location=(0,0)):
+    existing = nodes.get(name)
+    if existing is not None:
+        return existing
+    new_node = nodes.new('ShaderNodeTexImage')
+    new_node.name = name
+    new_node.location = location
+    return new_node
+
+def load_map_image(node, img_path, name, colorspace="sRGB"):
+    existing = bpy.data.images.get(name)
+    if existing is not None:
+         bpy.data.images.remove(existing)
+    node.image = bpy.data.images.load(img_path)
+    node.image.colorspace_settings.name = colorspace
+    node.image.name = name
+
+bpy.context.scene.render.image_settings.file_format = "PNG"
+
+material = bpy.data.materials.get("BSDFPlane")
+
+# Set node tree editing
+material.use_nodes = True
+nodes = material.node_tree.nodes
+
+# Compositing nodes
+scene = bpy.context.scene
+scene.render.use_compositing = True
+
+# Get output nodes
+p_out = nodes['Principled Output']
+
+# Get principled BSDF node
+bsdf_node = nodes.get("Principled BSDF")
+
+normal_map_node = nodes.get("Normal Map")
+displacement_node = nodes.get("Displacement")
+scale_node = nodes.get("Scale")
+
+# Get background node
+bg_node = bpy.data.worlds['World'].node_tree.nodes["Background"]
+
+# Get camera
+obj_camera = bpy.data.objects["Camera"]
+# Get the camera data block
+camera_data = obj_camera.data
+
+for item_bc in [x for x in dset_dir.glob("**/basecolor.png")][:]:
+    item = item_bc.parent
+    
+    if (item/"renders/passes").exists() and len(list(Path(item/"renders/passes").glob('*'))) == 10:
+        continue
+
+    # Clear orphan data
+    bpy.ops.outliner.orphans_purge()
+
+    # Set maps paths
+    basecolor_path = str(item/"basecolor.png")
+    normal_path = str(item/"normal.png")
+    roughness_path = str(item/"roughness.png")
+    metallic_path = str(item/"metallic.png")
+    height_path = str(item/"displacement.png")
+
+    # Setup nodes
+    basecolor_node = nodes.get("Base Color")
+    load_map_image(basecolor_node, basecolor_path, name="BaseColor")
+
+    normal_node = nodes.get("Normal")
+    load_map_image(normal_node, normal_path, name="Normal", colorspace="Non-Color")
+
+    roughness_node = nodes.get("Roughness")
+    load_map_image(roughness_node, roughness_path, name="Roughness", colorspace="Non-Color")
+
+    metallic_node = nodes.get("Metallic")
+    load_map_image(metallic_node, metallic_path, name="Metallic", colorspace="Non-Color")
+
+    height_node = nodes.get("Height")
+    load_map_image(height_node, height_path, name="Height", colorspace="Non-Color")
+
+    scale_node = nodes.get("Scale")
+    
+    # Set render settings
+    render_folder = item/"renders/passes"
+    render_folder.mkdir(exist_ok=True, parents=True)
+
+    for hdri_i in range(5):
+        env_node = bpy.data.worlds['World'].node_tree.nodes[f"Env {hdri_i}"]
+        bpy.data.worlds['World'].node_tree.links.new(env_node.outputs['Color'], bg_node.inputs['Color'])
+        bpy.data.worlds['World'].node_tree.nodes[f"HDRIRotation"].outputs[0].default_value = random.random() * math.pi * 2
+
+        for render_pass in ["diffuse", "glossy"]:
+            if render_pass == "diffuse":
+                scene.node_tree.nodes.active = scene.node_tree.nodes["DiffusePass"]
+                scale_node.outputs[0].default_value = 1.0
+                camera_data.type = 'ORTHO'
+            elif render_pass == "glossy":
+                scene.node_tree.nodes.active = scene.node_tree.nodes['GlossyPass']
+                scale_node.outputs[0].default_value = 0.0
+                camera_data.type = 'PERSP'
+
+            # Render
+            bpy.context.scene.render.filepath = str(render_folder/f"render_{hdri_i:02d}_{render_pass}.png")
+            bpy.ops.render.render(write_still=True)
+
+
+# Execution command: blender.exe -b .\render_ambient.blend -P .\render_ambient.py -- ..\maps
\ No newline at end of file