first

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

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+# Python build
+.eggs/
+gradio.egg-info/*
+!gradio.egg-info/requires.txt
+!gradio.egg-info/PKG-INFO
+dist/
+*.pyc
+__pycache__/
+*.py[cod]
+*$py.class
+build/
+
+# JS build
+gradio/templates/frontend
+# Secrets
+.env
+
+# Gradio run artifacts
+*.db
+*.sqlite3
+gradio/launches.json
+flagged/
+gradio_cached_examples/
+
+# Tests
+.coverage
+coverage.xml
+test.txt
+
+# Demos
+demo/tmp.zip
+demo/files/*.avi
+demo/files/*.mp4
+
+# Etc
+.idea/*
+.DS_Store
+*.bak
+workspace.code-workspace
+*.h5
+.vscode/
+
+# log files
+.pnpm-debug.log
+venv/
+*.db-journal

README.md

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+---
+title: Depth Image to Autostereogram (Magic Eye)
+emoji: 👀 😵‍💫 👀 
+colorFrom: green
+colorTo: black
+sdk: gradio
+sdk_version: 2.9.4
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
+
+Depth Image to Autostereogram (Magic Eye)

app.py

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+from doctest import Example
+import gradio as gr
+from transformers import DPTFeatureExtractor, DPTForDepthEstimation
+import torch
+import numpy as np
+from PIL import Image, ImageOps
+from pathlib import Path
+import os
+import glob
+from autostereogram.sirds_converter import SirdsConverter
+from skimage import color
+
+feature_extractor = DPTFeatureExtractor.from_pretrained("Intel/dpt-large")
+model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large")
+
+stereo_converter = SirdsConverter()
+
+
+def process_image(image_path):
+    image_raw = Image.open(Path(image_path))
+
+    image = image_raw.resize(
+        (1280, int(1280 * image_raw.size[1] / image_raw.size[0])),
+        Image.Resampling.LANCZOS)
+
+    # prepare image for the model
+    encoding = feature_extractor(image, return_tensors="pt")
+
+    # forward pass
+    with torch.no_grad():
+        outputs = model(**encoding)
+        predicted_depth = outputs.predicted_depth
+
+    # interpolate to original size
+    prediction = torch.nn.functional.interpolate(
+        predicted_depth.unsqueeze(1),
+        size=image.size[::-1],
+        mode="bicubic",
+        align_corners=False,
+    ).squeeze()
+    output = prediction.cpu().numpy()
+    depth_image = (output * 255 / np.max(output)).astype('uint8')
+    depth_image_padded = np.array(ImageOps.pad(
+        Image.fromarray(depth_image), (1280, 720)))
+
+    stereo_image = stereo_converter.convert_depth_to_stereogram_with_sird(
+        depth_image_padded, False, 0.5).astype(np.uint8)
+
+    return [depth_image_padded, stereo_image]
+
+
+title = "Demo: zero-shot depth estimation with DPT + 3D Voxels reconstruction"
+description = "This demo is a variation from the original <a href='https://huggingface.co/spaces/nielsr/dpt-depth-estimation' target='_blank'>DPT Demo</a>. It uses the DPT model to predict the depth of an image and then reconstruct the 3D model as voxels."
+
+examples = sorted(glob.glob('examples/*.jpg'))
+
+iface = gr.Interface(fn=process_image,
+                     inputs=[
+                         gr.inputs.Image(
+                             type="filepath", label="Input Image")
+                     ],
+                     outputs=[
+                         gr.outputs.Image(label="Predicted Depth", type="pil"),
+                         gr.outputs.Image(label="Stereogram", type="pil")
+                     ],
+                     description=description,
+                     examples=examples,
+                     allow_flagging="never",
+                     #  cache_examples=False
+                     )
+
+if __name__ == "__main__":
+    iface.launch(debug=True, enable_queue=False)

packages.txt

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+libgl1-mesa-glx

requirements.txt

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+torch
+git+https://github.com/nielsrogge/transformers.git@add_dpt_redesign#egg=transformers
+numpy
+Pillow
+gradio==2.9.4
+jinja2
+transformers
+scikit-image
+pystereogram