Update app.py

app.py

@@ -1,59 +1,87 @@
-# # Top of main python script
-# import os
-# os.environ['PYOPENGL_PLATFORM'] = 'egl'
+import gradio as gr
+import pickle
+# from datasets import load_from_disk
+from plaid.containers.sample import Sample
+# import pyvista as pv
 
-# import pyrender
-# import numpy as np
+import pyrender
+import trimesh
+import matplotlib.pyplot as plt
 
-# r = pyrender.OffscreenRenderer(viewport_width=640,
-#                                 viewport_height=480,
-#                                 point_size=1.0)
+import os
+# switch to "osmesa" or "egl" before loading pyrender
+os.environ["PYOPENGL_PLATFORM"] = "egl"
 
-# cam = pyrender.PerspectiveCamera(yfov=np.pi / 3.0, aspectRatio=1.414)
+import numpy as np
 
-# scene = pyrender.Scene(ambient_light=[0.02, 0.02, 0.02],
-#                         bg_color=[1.0, 1.0, 1.0])
+# FOLDER = "plot"
 
-# scene.add(cam, pose=np.eye(4))
-# color, depth = r.render(scene)
+# dataset = load_from_disk("Rotor37")
 
-# print(color)
-# print(depth)
+field_names_train = ["Temperature", "Pressure", "Density"]#pickle.loads(dataset[0]["sample"]).get_field_names()
+field_names_test  = []
 
 
-import os
-# switch to "osmesa" or "egl" before loading pyrender
-os.environ["PYOPENGL_PLATFORM"] = "egl"
 
-import numpy as np
-import pyrender
-import trimesh
-import matplotlib.pyplot as plt
 
-# generate mesh
-sphere = trimesh.creation.icosphere(subdivisions=4, radius=0.8)
-sphere.vertices+=1e-2*np.random.randn(*sphere.vertices.shape)
-mesh = pyrender.Mesh.from_trimesh(sphere, smooth=False)
 
-# compose scene
-scene = pyrender.Scene(ambient_light=[.1, .1, .3], bg_color=[0, 0, 0])
-camera = pyrender.PerspectiveCamera( yfov=np.pi / 3.0)
-light = pyrender.DirectionalLight(color=[1,1,1], intensity=2e3)
 
-scene.add(mesh, pose=  np.eye(4))
-scene.add(light, pose=  np.eye(4))
 
-c = 2**-0.5
-scene.add(camera, pose=[[ 1,  0,  0,  0],
-                        [ 0,  c, -c, -2],
-                        [ 0,  c,  c,  2],
-                        [ 0,  0,  0,  1]])
+def sample_info(sample_id_str, fieldn):
+
+    sample_id = int(sample_id_str)
+
+    plaid_sample = Sample.load_from_dir(f"Rotor37/dataset/samples/sample_"+str(sample_id_str).zfill(9))
+    
+    
+    # generate mesh
+    sphere = trimesh.creation.icosphere(subdivisions=4, radius=0.8)
+    sphere.vertices+=1e-2*np.random.randn(*sphere.vertices.shape)
+    mesh = pyrender.Mesh.from_trimesh(sphere, smooth=False)
+    
+    # compose scene
+    scene = pyrender.Scene(ambient_light=[.1, .1, .3], bg_color=[0, 0, 0])
+    camera = pyrender.PerspectiveCamera( yfov=np.pi / 3.0)
+    light = pyrender.DirectionalLight(color=[1,1,1], intensity=2e3)
+    
+    scene.add(mesh, pose=  np.eye(4))
+    scene.add(light, pose=  np.eye(4))
+    
+    c = 2**-0.5
+    scene.add(camera, pose=[[ 1,  0,  0,  0],
+                            [ 0,  c, -c, -2],
+                            [ 0,  c,  c,  2],
+                            [ 0,  0,  0,  1]])
+    
+    # render scene
+    r = pyrender.OffscreenRenderer(512, 512)
+    color, _ = r.render(scene)
+    
+    plt.figure(figsize=(8,8))
+    plt.imshow(color)
+    
+    plt.savefig("test.png")
+
+
+
+    return str__, "test.png"
+
+
+if __name__ == "__main__":
+
+    with gr.Blocks() as demo:
+        d1 = gr.Slider(0, 999, value=0, label="Training sample id", info="Choose between 0 and 999")
+        d2 = gr.Dropdown(field_names_train, value=field_names_train[0], label="Field name")
+
+
+        output1 = gr.Text(label="Training sample info")
+        output2 = gr.Image(label="Training sample visualization")
+
+        # d1.input(update_second, d1, d2)
+
+        d1.input(sample_info, [d1, d2], [output1, output2])
+        d2.input(sample_info, [d1, d2], [output1, output2]) 
 
-# render scene
-r = pyrender.OffscreenRenderer(512, 512)
-color, _ = r.render(scene)
 
-plt.figure(figsize=(8,8))
-plt.imshow(color)
+    demo.launch()
 
-plt.savefig("test.png")