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app.py

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+data_path = "./data/"
+
+import pandas as pd
+
+# load the csv into motion_capture_data
+
+import streamlit as st
+st.title("CyberOrigin Data Visualization")
+dataset_option = st.sidebar.selectbox(
+    'Select a dataset:',
+    ['Fold_towels', 'Pipette', 'Take_the_item', 'Twist_the_tube']
+)
+motion_capture_path = data_path+dataset_option +"/motionCaptureData.csv"
+video_path = data_path+dataset_option+"/video.mp4"
+motion_capture_data = pd.read_csv(motion_capture_path)
+# create a streamlit app that displays the motion capture data
+# and the video data
+st.video(video_path)
+
+body_part_names = ['Left Shoulder',
+ 'Right Upper Arm',
+ 'Left Lower Leg',
+ 'Spine1',
+ 'Right Upper Leg',
+ 'Spine3',
+ 'Right Lower Arm',
+ 'Left Foot',
+ 'Right Lower Leg',
+ 'Right Shoulder',
+ 'Left Hand',
+ 'Left Upper Leg',
+ 'Right Foot',
+ 'Spine',
+ 'Spine2',
+ 'Left Lower Arm',
+ 'Left Toe',
+ 'Neck',
+ 'Right Hand',
+ 'Right Toe',
+ 'Head',
+ 'Left Upper Arm',
+ 'Hips',]
+
+motion_capture_x = motion_capture_data[[body_part_name+"_x" for body_part_name in body_part_names]]
+motion_capture_y = motion_capture_data[[body_part_name+"_y" for body_part_name in body_part_names]]
+motion_capture_z = motion_capture_data[[body_part_name+"_z" for body_part_name in body_part_names]]
+
+import plotly.graph_objects as go
+import numpy as np
+
+# Sample Data Preparation
+data = []
+times = motion_capture_data["timestamp"]
+frames = [go.Frame(
+    data=[
+        go.Scatter3d(
+            x=motion_capture_x.iloc[k],
+            y=motion_capture_y.iloc[k],
+            z=motion_capture_z.iloc[k],
+            mode='markers',
+            marker=dict(size=5, color='blue')
+        )
+    ],
+    name=str(k)
+) for k in range(len(times))]
+
+# Create the initial scatter plot
+initial_scatter = go.Scatter3d(
+    x=motion_capture_x.iloc[0],
+    y=motion_capture_y.iloc[0],
+    z=motion_capture_z.iloc[0],
+    mode='markers',
+    marker=dict(size=5, color='blue')
+)
+
+# Create the layout with slider
+layout = go.Layout(
+    title='Motion Capture Visualization',
+    updatemenus=[{
+        'buttons': [
+            {
+                'args': [None, {'frame': {'duration': 1, 'redraw': True}, 'fromcurrent': True}],
+                'label': 'Play',
+                'method': 'animate'
+            },
+            {
+                'args': [[None], {'frame': {'duration': 0, 'redraw': True}, 'mode': 'immediate', 'transition': {'duration': 0}}],
+                'label': 'Pause',
+                'method': 'animate'
+            }
+        ],
+        'direction': 'left',
+        'pad': {'r': 10, 't': 87},
+        'showactive': True,
+        'type': 'buttons',
+        'x': 0.1,
+        'xanchor': 'right',
+        'y': 0,
+        'yanchor': 'top'
+    }],
+    sliders=[{
+        'active': 0,
+        'steps': [{
+            'label': str(k),
+            'method': 'animate',
+            'args': [
+                [str(k)],
+                {'mode': 'immediate', 'frame': {'duration': 300, 'redraw': True}, 'transition': {'duration': len(times)/30}}
+            ]
+        } for k in range(len(times))],
+        'currentvalue': {
+            'prefix': 'Time: ',
+            'visible': True,
+            'xanchor': 'right'
+        },
+        'pad': {'b': 10},
+        'len': 0.9,
+        'x': 0.1,
+        'y': 0,
+    }]
+)
+
+# Create the figure
+fig = go.Figure(data=[initial_scatter], frames=frames, layout=layout)
+
+# Display the figure in the streamlit app
+st.plotly_chart(fig)

requirements.txt

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+streamlit
+pandas
+plotly
+numpy