update layout with embed4d viewer

.gitattributes

@@ -6,6 +6,7 @@
 *.c3d filter=lfs diff=lfs merge=lfs -text
 *.ftz filter=lfs diff=lfs merge=lfs -text
 *.gz filter=lfs diff=lfs merge=lfs -text
+*.glb 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

README.md

@@ -1,6 +1,6 @@
 ---
 title: Myosdk App
-emoji: 😻
+emoji: 🏃
 colorFrom: green
 colorTo: gray
 sdk: gradio

app.py

@@ -17,10 +17,13 @@ import time
 
 import cv2
 import gradio as gr
+import myosdk
 import numpy as np
+import pandas as pd
 import plotly.graph_objs as go
 import spaces
 import torch
+from embed4d import model3d_viewer
 from metrabs_pytorch.scripts.run_video import run_metrabs_video
 from myo_tools.mjs.marker.marker_api import get_marker_names
 from myo_tools.utils.file_ops.dataframe_utils import from_array_to_dataframe
@@ -38,6 +41,9 @@ PLOT_CONFIG = {
 
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+UPLOAD_GLB = os.path.join(os.path.dirname(__file__), "./info_files/upload_files.glb")
+ERROR_GLB = os.path.join(os.path.dirname(__file__), "./info_files/error.glb")
+PROCESSING_GLB = os.path.join(os.path.dirname(__file__), "./info_files/processing.glb")
 
 
 def draw_keypoints(frame, poses2d, radius=10):
@@ -69,15 +75,6 @@ def save_video_with_keypoints(results, output_video):
     return output_video
 
 
-def load_all_videos():
-    video_dir = os.path.join(os.path.dirname(__file__), "./data")
-    return [
-        os.path.abspath(os.path.join(video_dir, f))
-        for f in os.listdir(video_dir)
-        if f.lower().endswith((".mp4", ".avi", ".mov", ".mkv"))
-    ]
-
-
 def create_info_text(title, info_text):
     return f"""
     <div>
@@ -157,7 +154,7 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
                 None,
                 gr.update(value=[], visible=True),
                 gr.update(visible=False),
-                gr.update(visible=False),
+                gr.update(visible=True, value=model3d_viewer(ERROR_GLB)),
             )
             return
 
@@ -168,7 +165,7 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
             None,
             gr.update(value=[], visible=True),
             gr.update(visible=False),
-            gr.update(visible=False),
+            gr.update(visible=True, value=model3d_viewer(ERROR_GLB)),
         )
 
     try:
@@ -177,7 +174,7 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
         init_time = time.time()
         yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
             visible=False
-        ), gr.update(visible=False)
+        ), gr.update(visible=True, value=model3d_viewer(PROCESSING_GLB)),
         client = Client(api_key=api_key)
 
         status.append(
@@ -188,7 +185,7 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
         status.append("🔹 Uploading markerset file...")
         yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
             visible=False
-        ), gr.update(visible=False)
+        ), gr.update(visible=True, value=model3d_viewer(PROCESSING_GLB)),
         mk_asset = client.assets.upload_file(markerset_file.name)
 
         status.append(
@@ -196,7 +193,7 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
         )
         yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
             visible=False
-        ), gr.update(visible=False)
+        ), gr.update(visible=True, value=model3d_viewer(PROCESSING_GLB)),
 
         mk_id = mk_asset["asset_id"]
 
@@ -209,7 +206,7 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
 
             yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
                 visible=False
-            ), gr.update(visible=False)
+            ), gr.update(visible=True, value=model3d_viewer(PROCESSING_GLB)),
 
             init_time = time.time()
             tracker_asset = client.assets.upload_file(f)
@@ -218,7 +215,7 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
             )
             yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
                 visible=False
-            ), gr.update(visible=False)
+            ), gr.update(visible=True, value=model3d_viewer(PROCESSING_GLB)),
             init_time = time.time()
             job = client.jobs.start_retarget(
                 tracker_asset_id=tracker_asset["asset_id"],
@@ -231,16 +228,16 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
             )
             yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
                 visible=False
-            ), gr.update(visible=False)
+            ), gr.update(visible=True, value=model3d_viewer(PROCESSING_GLB)),
             init_time = time.time()
             result = client.jobs.wait(job["job_id"])
 
             status.append(
                 f"\t🔹 Retargeting job completed in {time.time() - init_time:.2f} seconds"
-            ), gr.update(visible=False),
+            )
             yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
                 visible=False
-            ), gr.update(visible=False)
+            ), gr.update(visible=True, value=model3d_viewer(PROCESSING_GLB)),
             assert (
                 result["status"] == "SUCCEEDED"
             ), f"Failed retarget for {os.path.basename(f)}"
@@ -271,21 +268,26 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
         time.sleep(0.1)  # allow filesystem flush
         yield "\n".join(status), None, None, gr.update(
             interactive=True, visible=True
-        ), gr.update(visible=True), gr.update(visible=True, value=output_glb_files[0])
-
+        ), gr.update(visible=True), gr.update(
+            visible=True, value=model3d_viewer(output_glb_files[0])
+        )
+        assert os.path.exists(out_path)
         df = from_qpos_to_joint_angles(output_files[0])
 
         angle_list = list(df.columns[1:])
         initial_value = [angle_list[0]] if angle_list else []
-
+        initial_plot = update_plot(df, initial_value)
         status.append("✅ Complete!")
+        df_state_path = os.path.abspath(output_files[0])
         yield (
             "\n".join(status),
             gr.update(value=output_files, visible=True),
-            df,
-            gr.update(choices=angle_list, value=initial_value, visible=True),
-            gr.update(visible=True),
-            gr.update(visible=True, value=output_glb_files[0]),
+            df_state_path,  # Use absolute path for Linux compatibility
+            gr.update(
+                choices=angle_list, value=initial_value, visible=True, interactive=True
+            ),
+            gr.update(value=initial_plot, visible=True),
+            gr.update(visible=True, value=model3d_viewer(output_glb_files[0])),
         )
 
     except Exception as e:
@@ -295,7 +297,7 @@ def run_retargeting_c3d(api_key, c3d_files, markerset_file):
             None,
             gr.update(visible=False),
             gr.update(visible=False),
-            gr.update(visible=False),
+            gr.update(visible=True, value=model3d_viewer(ERROR_GLB)),
         )
 
 
@@ -319,7 +321,7 @@ def run_retargeting_video(
                 gr.update(visible=False),
                 gr.update(visible=False),
                 video_file,
-                gr.update(visible=False),
+                gr.update(visible=True, value=model3d_viewer(ERROR_GLB)),
             )
             return
 
@@ -341,7 +343,7 @@ def run_retargeting_video(
             gr.update(visible=False),
             gr.update(visible=False),
             video_file,
-            gr.update(visible=False),
+            gr.update(visible=True, value=model3d_viewer(ERROR_GLB)),
         )
         return
 
@@ -354,7 +356,7 @@ def run_retargeting_video(
         init_time = time.time()
         yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
             visible=False
-        ), video_path, gr.update(visible=False)
+        ), video_path, gr.update(visible=True, value=model3d_viewer(PROCESSING_GLB)),
 
         results = list(
             run_metrabs_video(video_path=video_path, device=DEVICE, visualize=False)
@@ -363,6 +365,8 @@ def run_retargeting_video(
             np.array([res["poses3d"] for res in results]).squeeze()
         )
 
+        markers[:, :, 2] = markers[:, :, 2] - np.min(markers[:, :, 2])
+
         fps = (
             results[0]["fps"] if results else 25.0
         )  # Default to 25 fps if not available
@@ -374,20 +378,26 @@ def run_retargeting_video(
 
         yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
             visible=True
-        ), video_with_keypoints, gr.update(visible=False)
+        ), video_with_keypoints, gr.update(
+            visible=True, value=model3d_viewer(PROCESSING_GLB)
+        ),
         status.append(
             f"🔹 Pose Extraction from Video Completed in {time.time() - init_time:.2f} seconds with {len(markers)} frames extracted ({((time.time() - init_time)/len(markers)):.2f} seconds per frame)"
         )
         print("🔹 Pose Extraction from Video Completed")
-        yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
+        yield "\n".join(status), None, None, None, gr.update(
             visible=False
-        ), video_with_keypoints, gr.update(visible=False)
+        ), video_with_keypoints, gr.update(
+            visible=True, value=model3d_viewer(PROCESSING_GLB)
+        ),
         # Initialize client
         status.append("🔹 Initializing MyoSDK client...")
         init_time = time.time()
         yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
             visible=False,
-        ), video_with_keypoints, gr.update(visible=False)
+        ), video_with_keypoints, gr.update(
+            visible=True, value=model3d_viewer(PROCESSING_GLB)
+        ),
         client = Client(api_key=api_key)
 
         status.append(
@@ -396,9 +406,11 @@ def run_retargeting_video(
         init_time = time.time()
         # Upload markerset
         status.append("🔹 Uploading markerset file...")
-        yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
+        yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
             visible=False,
-        ), video_with_keypoints, gr.update(visible=False)
+        ), video_with_keypoints, gr.update(
+            visible=True, value=model3d_viewer(PROCESSING_GLB)
+        ),
 
         markerset_file_name = "markersets/movi_metrabs_markerset.xml"
 
@@ -408,9 +420,11 @@ def run_retargeting_video(
             f"🔹 Markerset file uploaded in {time.time() - init_time:.2f} seconds"
         )
 
-        yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
+        yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
             visible=False
-        ), video_with_keypoints, gr.update(visible=False)
+        ), video_with_keypoints, gr.update(
+            visible=True, value=model3d_viewer(PROCESSING_GLB)
+        ),
         init_time = time.time()
 
         marker_names = get_marker_names(markerset_file_name)
@@ -440,16 +454,20 @@ def run_retargeting_video(
         )
         yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
             visible=False
-        ), video_with_keypoints, gr.update(visible=False)
+        ), video_with_keypoints, gr.update(
+            visible=True, value=model3d_viewer(PROCESSING_GLB)
+        ),
         init_time = time.time()
         result = client.jobs.wait(job["job_id"])
 
         status.append(
             f"\t🔹 Retargeting job completed in {time.time() - init_time:.2f} seconds"
         )
-        yield "\n".join(status), None, None, gr.update(value=[]), gr.update(
+        yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
             visible=False
-        ), video_with_keypoints, gr.update(visible=False)
+        ), video_with_keypoints, gr.update(
+            visible=True, value=model3d_viewer(PROCESSING_GLB)
+        ),
 
         print("STATUS: ", result["status"])
         assert (
@@ -471,29 +489,36 @@ def run_retargeting_video(
             result["output"]["retarget_output_asset_ids"]["motion"], output_glb_path
         )
 
+        assert os.path.getsize(output_glb_path) > 0
+        time.sleep(0.1)  # allow filesystem flush
+        print("output_glb_path: ", output_glb_path, os.path.getsize(output_glb_path))
         # Load angles from first output file
         status.append("🔹 Loading animation and angle data...")
-        yield "\n".join(status), None, None, gr.update(
-            interactive=True, visible=True
-        ), gr.update(visible=True), video_with_keypoints, gr.update(
-            visible=True, value=output_glb_path
+        yield "\n".join(status), None, None, gr.update(visible=False), gr.update(
+            visible=True
+        ), video_with_keypoints, gr.update(
+            visible=True, value=model3d_viewer(output_glb_path)
         )
-
+        assert os.path.exists(out_path)
         df = from_qpos_to_joint_angles(out_path)
 
         angle_list = list(df.columns[1:])
         initial_value = [angle_list[0]] if angle_list else []
-
+        initial_plot = update_plot(df, initial_value)
         status.append("✅ Complete!")
+        df_state_path = os.path.abspath(out_path)
         yield (
             "\n".join(status),
             gr.update(value=out_path, visible=True),
-            df,
-            gr.update(choices=angle_list, value=initial_value, visible=True),
-            gr.update(visible=True),
+            df_state_path,  # Use absolute path for Linux compatibility
+            gr.update(
+                choices=angle_list, value=initial_value, visible=True, interactive=True
+            ),
+            gr.update(value=initial_plot, visible=True),
             video_with_keypoints,
-            gr.update(visible=True, value=output_glb_path),
+            gr.update(visible=True, value=model3d_viewer(output_glb_path)),
         )
+        return
 
     except Exception as e:
         # Use video_path if defined, otherwise use video_file or None
@@ -509,17 +534,41 @@ def run_retargeting_video(
             gr.update(visible=False),
             gr.update(visible=False),
             error_video,
+            gr.update(visible=True, value=model3d_viewer(ERROR_GLB)),
         )
 
 
 # ------------------------------------------------------------
 # Plotting
 # ------------------------------------------------------------
-def update_plot(df, joints):
-    if df is None or df.empty:
-        return go.Figure()
+
+
+def update_plot(parquet_path, joints):
+    """Safe Linux/macOS plotting from parquet or DataFrame."""
+    # Check joints first to avoid unnecessary processing
     if not joints:
         return go.Figure()
+
+    # Check if parquet_path is valid
+    if parquet_path is None:
+        return go.Figure()
+
+    if isinstance(parquet_path, pd.DataFrame):
+        df = parquet_path
+    else:
+        # Nothing loaded yet - check if it's an empty string
+        if parquet_path == "":
+            return go.Figure()
+
+        # File might not exist yet (race-safe)
+        if not os.path.exists(parquet_path):
+            return go.Figure()
+
+        df = pd.read_parquet(parquet_path)
+
+    if df is None or df.empty:
+        return go.Figure()
+
     if not isinstance(joints, list):
         joints = [joints]
 
@@ -534,25 +583,28 @@ def update_plot(df, joints):
         yaxis_title="Angle Value (degrees)",
         plot_bgcolor="#1E1E1E",
         paper_bgcolor="#1E1E1E",
-        font=dict(color="#F0F0F0", family="Arial"),
-        xaxis=dict(gridcolor="#444444", linecolor="#F0F0F0", tickcolor="#F0F0F0"),
-        yaxis=dict(gridcolor="#444444", linecolor="#F0F0F0", tickcolor="#F0F0F0"),
-        legend=dict(font=dict(color="#F0F0F0")),
+        font=dict(color="#F0F0F0"),
+        xaxis=dict(gridcolor="#444444"),
+        yaxis=dict(gridcolor="#444444"),
+        dragmode="pan",
     )
+
     return fig
 
 
-with gr.Blocks() as app:
+CSS = """
+.left-panel, .right-panel { background-color: #1E1E1E; border:1px solid var(--border-color, #e9ecef) !important; border-radius:15px !important; box-shadow:0 4px 20px rgba(0,0,0,.08) !important; padding:12px !important; }
+"""
+with gr.Blocks(css=CSS) as app:
 
     with gr.Row():
         with gr.Column(scale=3):
             gr.Markdown(
                 """
-                ## MyoSDK Kinesis
-                <span style="color:#6b7280">Joint visualization & motion retargeting pipelines</span>
+                ## <a href="https://myolab.ai/blog/myokinesis">MyoKinesis</a>
+                <span style="color:#6b7280">High-Fidelity Human Motion Reconstruction for Developers, Researchers, and Builders</span>
 
-                This application allows you to retarget motion capture data to biomechanical models using MyoSDK's Kinesis engine.
-                Upload C3D files or videos to extract joint angles using [Kinesis](https://myolab.ai/blog/myokinesis) and visualize motion data.
+                Reconstruct anatomically accurate human motion from uploaded C3D or video data using MyoKinesis.
                 """
             )
         with gr.Column(scale=1):
@@ -562,88 +614,91 @@ with gr.Blocks() as app:
                 type="password",
                 info="Get your API key from https://dev.myolab.ai",
             )
-    with gr.Tab("📊 Motion Capture Retargeting"):
-
-        gr.Markdown(
-            """
-            Upload motion capture data in C3D format along with a markerset XML file to retarget the motion to a biomechanical model.
-            The process will extract joint angles and generate visualizations of the motion data.
-            """
-        )
-        with gr.Row(equal_height=True):
-            with gr.Column(scale=2):
-                gr.HTML(
-                    create_info_text(
-                        "1. Upload a Markerset File",
-                        "Upload an XML file that defines the marker set configuration. This file specifies which markers are used and their anatomical locations."
-                        + 'See <a href="https://markerset-editor.myolab.ai">Markerset Editor</a> for more details.',
-                    )
-                )
-
-                markerset = gr.File(
-                    # label=None,
-                    file_types=[".xml"],
-                    elem_id="file-upload-markerset",
+    with gr.Row(height=550):
+        with gr.Row(height=530, elem_classes=["left-panel"]):
+            with gr.Tab("📊 MoCap"):
+                with gr.Row():
+                    with gr.Column(scale=2):
+                        gr.HTML(
+                            create_info_text(
+                                "1. Upload a Markerset File",
+                                "Upload an XML file that defines the marker set configuration. This file specifies which markers are used and their anatomical locations."
+                                + 'See <a href="https://markerset-editor.myolab.ai">Markerset Editor</a> for more details.',
+                            )
+                        )
+
+                        markerset = gr.File(
+                            # label=None,
+                            file_types=[".xml"],
+                            elem_id="file-upload-markerset",
+                            value=os.path.join(
+                                os.path.dirname(__file__),
+                                "../markersets/cmu_markerset.xml",
+                            ),
+                        )
+
+                        gr.HTML(
+                            create_info_text(
+                                "2. Upload C3D Motion Capture File(s)",
+                                "Upload one or more C3D files containing 3D marker trajectories from motion capture systems."
+                                + 'Example from CMU dataset: <a href="https://mocap.cs.cmu.edu/subjects/35/35_30.c3d">35_30.c3d</a>',
+                            )
+                        )
+                        c3d_files = gr.File(
+                            label=None,
+                            file_types=[".c3d"],
+                            elem_id="file-upload-c3d",
+                            file_count="multiple",
+                            value=[
+                                os.path.join(
+                                    os.path.dirname(__file__), "./data/35_30.c3d"
+                                )
+                            ],
+                        )
+
+                        run_btn_c3d = gr.Button(
+                            "3. 🚀 Run Retargeting", variant="primary"
+                        )
+
+            with gr.Tab("🎥 Video"):
+                video_file = gr.Video(
+                    label="1. Upload a Video File (Supported formats: MP4, AVI, MOV, MKV)",
+                    height=300,
                     value=os.path.join(
-                        os.path.dirname(__file__), "./markersets/cmu_markerset.xml"
+                        os.path.dirname(__file__),
+                        "./data/5385885.mp4",
                     ),
                 )
-
-            with gr.Column(scale=2):
-                gr.HTML(
-                    create_info_text(
-                        "2. Upload C3D Motion Capture File(s)",
-                        "Upload one or more C3D files containing 3D marker trajectories from motion capture systems."
-                        + 'Example from CMU dataset: <a href="https://mocap.cs.cmu.edu/subjects/35/35_30.c3d">35_30.c3d</a>',
-                    )
+                run_v2m_btn_video = gr.Button(
+                    "2. 🚀 Run Retargeting from Video", variant="primary"
                 )
-                c3d_files = gr.File(
-                    label=None,
-                    file_types=[".c3d"],
-                    elem_id="file-upload-c3d",
-                    file_count="multiple",
-                    value=[
-                        os.path.join(os.path.dirname(__file__), "./data/35_30.c3d")
-                    ],
+                gr.Markdown(
+                    """
+                    ⚠️ **Important:** Using Metrabs for video motion retargeting **ONLY FOR RESEARCH/ACADEMIC USE**.
+                    Please cite the [paper](https://arxiv.org/abs/2007.07227).
+                    For commercial applications, contact `contacts@myolab.ai`
+                    """
                 )
-
-        run_btn_c3d = gr.Button("3. 🚀 Run Retargeting", variant="primary")
-
-    with gr.Tab("🎥 Video-Based Motion Retargeting"):
-        gr.Markdown(
-            """
-            Extract 3D pose from video and retarget it to a biomechanical model using [Kinesis](https://myolab.ai/blog/myokinesis).
-
-            ⚠️ **Important:** Using Metrabs for video-based motion retargeting which is **ONLY FOR RESEARCH/ACADEMIC USE**.
-            Please cite the [paper](https://arxiv.org/abs/2007.07227) if you use this feature.
-            For commercial applications, please contact MyoLab at contacts@myolab.ai.
-            """
-        )
-        video_file = gr.Video(
-            label="1. Upload a Video File (Supported formats: MP4, AVI, MOV, MKV)",
-            height=400,
-            value=os.path.join(
-                os.path.dirname(__file__), "./data/13710671_1080_1920_25fps.mp4"
-            ),
-        )
-        run_v2m_btn_video = gr.Button(
-            "2. 🚀 Run Retargeting from Video", variant="primary"
-        )
-
-    output_3d_motion = gr.Model3D(
-        label="3D Motion Visualization",
-        visible=False,
-    )
+        with gr.Row(height=530, elem_classes=["right-panel"]):
+            output_3d_motion = gr.HTML(
+                label="3D Motion Visualization",
+                visible=True,
+                value=model3d_viewer(
+                    UPLOAD_GLB,
+                    height=500,
+                ),
+            )
     output_file = gr.File(
         label="📥 Download Results - Download the retargeted motion data as a Parquet (.parquet) file containing joint angles and metadata.",
-        visible=False,
+        visible=True,
     )
     df_state = gr.State()
     joint_dropdown = gr.Dropdown(
         label="Select Joint Angle(s) to Visualize",
-        interactive=False,
+        choices=[],
+        interactive=True,
         multiselect=True,
-        visible=True,
+        visible=False,  # Hidden initially, shown only when data is ready
         info="After processing completes, select one or more joint angles to plot. The dropdown will be populated with available joints from the retargeted data.",
     )
     plot_area = gr.Plot(
@@ -655,11 +710,40 @@ with gr.Blocks() as app:
         lines=12,
         info="Real-time status updates showing the progress of file uploads, retargeting jobs, and data processing.",
     )
+    gr.Markdown(f"MyoSDK v{myosdk.__version__}")
+
+    def update_plot_wrapper(parquet_path, joints):
+        """Wrapper to ensure plot is visible and updated on Linux."""
+        if not joints:
+            return gr.update(value=go.Figure(), visible=False)
+
+        if parquet_path is None:
+            return gr.update(value=go.Figure(), visible=False)
+
+        # Check if file exists and convert to absolute path for consistency
+        if isinstance(parquet_path, str):
+            if not os.path.exists(parquet_path):
+                return gr.update(value=go.Figure(), visible=False)
+            parquet_path = os.path.abspath(parquet_path)
+
+        try:
+            fig = update_plot(parquet_path, joints)
+            return gr.update(value=fig, visible=True)
+        except Exception:
+            return gr.update(value=go.Figure(), visible=False)
 
     joint_dropdown.change(
-        fn=update_plot,
+        fn=update_plot_wrapper,
+        inputs=[df_state, joint_dropdown],
+        outputs=[plot_area],
+        show_progress=False,
+    )
+
+    joint_dropdown.input(
+        fn=update_plot_wrapper,
         inputs=[df_state, joint_dropdown],
         outputs=[plot_area],
+        show_progress=False,
     )
     run_btn_c3d.click(
         fn=run_retargeting_c3d,

data/5385885.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:615a11bd65c7d1e3af4c309f00335e3be464b7ecb9e6b3bbc354ca80c6df338c
+size 690209

info_files/error.glb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dcefaeeee6ee7a94c2a8f582af1466e21460bc5f8e4fb0f47e33670cb8288711
+size 237300

info_files/processing.glb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e3615d2ef57ca201a359d9d66c595783f8921b873d96635c915959d0ff147412
+size 640944

info_files/upload_files.glb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:441bd0d6b6265e38c9686e929f694dc84ca9ebe3810a3446adb0a2ea737299e0
+size 247132

requirements.txt

@@ -3,4 +3,5 @@ plotly
 myosdk>=0.1.0
 myo_tools
 git+https://github.com/Vittorio-Caggiano/metrabs.git
-spaces
+spaces
+embed4d