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fabiencasenave
commited on
Commit
•
32ff3c8
1
Parent(s):
45cdafe
Update app.py
Browse files
app.py
CHANGED
@@ -35,37 +35,38 @@ def sample_info(sample_id_str, fieldn):
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str__ = f"loading sample {sample_id_str}"
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# generate mesh
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sphere = trimesh.creation.icosphere(subdivisions=4, radius=0.8)
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sphere.vertices+=1e-2*np.random.randn(*sphere.vertices.shape)
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mesh = pyrender.Mesh.from_trimesh(sphere, smooth=False)
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# compose scene
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scene = pyrender.Scene(ambient_light=[.1, .1, .3], bg_color=[0, 0, 0])
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camera = pyrender.PerspectiveCamera( yfov=np.pi / 3.0)
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light = pyrender.DirectionalLight(color=[1,1,1], intensity=2e3)
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scene.add(mesh, pose= np.eye(4))
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scene.add(light, pose= np.eye(4))
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c = 2**-0.5
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scene.add(camera, pose=[[ 1, 0, 0, 0],
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# render scene
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r = pyrender.OffscreenRenderer(512, 512)
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color, _ = r.render(scene)
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plt.figure(figsize=(8,8))
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plt.imshow(color)
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plt.savefig("test.png")
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return str__, "test.png"
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if __name__ == "__main__":
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@@ -76,7 +77,8 @@ if __name__ == "__main__":
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output1 = gr.Text(label="Training sample info")
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output2 = gr.
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# d1.input(update_second, d1, d2)
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str__ = f"loading sample {sample_id_str}"
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# # generate mesh
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# sphere = trimesh.creation.icosphere(subdivisions=4, radius=0.8)
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# sphere.vertices+=1e-2*np.random.randn(*sphere.vertices.shape)
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# mesh = pyrender.Mesh.from_trimesh(sphere, smooth=False)
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# # compose scene
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# scene = pyrender.Scene(ambient_light=[.1, .1, .3], bg_color=[0, 0, 0])
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# camera = pyrender.PerspectiveCamera( yfov=np.pi / 3.0)
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# light = pyrender.DirectionalLight(color=[1,1,1], intensity=2e3)
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# scene.add(mesh, pose= np.eye(4))
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# scene.add(light, pose= np.eye(4))
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# c = 2**-0.5
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# scene.add(camera, pose=[[ 1, 0, 0, 0],
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# [ 0, c, -c, -2],
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# [ 0, c, c, 2],
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# [ 0, 0, 0, 1]])
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# # render scene
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# r = pyrender.OffscreenRenderer(512, 512)
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# color, _ = r.render(scene)
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# plt.figure(figsize=(8,8))
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# plt.imshow(color)
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# plt.savefig("test.png")
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# return str__, "test.png"
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return str__, str__
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if __name__ == "__main__":
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output1 = gr.Text(label="Training sample info")
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output2 = gr.Text(label="Training sample visualization")
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# output2 = gr.Image(label="Training sample visualization")
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# d1.input(update_second, d1, d2)
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