Update app.py

app.py

@@ -1,83 +1,14 @@
-import os
-import sys
-import gradio as gr
-import torch
+import pyrender
 import numpy as np
-from transformers import Wav2Vec2Processor
-from visualise.rendering import RenderTool
-from data_utils import torch_data
-from trainer.options import parse_args
-from trainer.config import load_JsonConfig
-from nets import init_model, infer  # Ensure these functions are properly defined
+import trimesh
 
-# Set environment variables
-os.environ['PYOPENGL_PLATFORM'] = 'egl'
-os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-sys.path.append(os.getcwd())
+# Create a simple mesh
+mesh = trimesh.Sphere(radius=1.0)
+mesh = pyrender.Mesh.from_trimesh(mesh)
 
-# Load the model and configuration
-def load_models(config_file, face_model_name, face_model_path, body_model_name, body_model_path):
-    args = parse_args()
-    config = load_JsonConfig(config_file)
-    
-    # Initialize models
-    generator_face = init_model(face_model_name, face_model_path, args, config)
-    generator_body = init_model(body_model_name, body_model_path, args, config)
+# Create a scene and add the mesh
+scene = pyrender.Scene()
+scene.add(mesh)
 
-    # Initialize SMPL-X model
-    smplx_model_params = {
-        'model_path': './visualise/',
-        'model_type': 'smplx',
-        'create_global_orient': True,
-        'create_body_pose': True,
-        'create_betas': True,
-        'num_betas': 300,
-        'create_left_hand_pose': True,
-        'create_right_hand_pose': True,
-        'use_pca': False,
-        'flat_hand_mean': False,
-        'create_expression': True,
-        'num_expression_coeffs': 100,
-        'num_pca_comps': 12,
-        'create_jaw_pose': True,
-        'create_leye_pose': True,
-        'create_reye_pose': True,
-        'create_transl': False,
-        'dtype': torch.float64,
-    }
-    smplx_model = smpl.create(**smplx_model_params).to('cuda')
-    
-    return generator_face, generator_body, smplx_model, config
-
-# Inference function
-def run_inference(audio_file):
-    # Load models
-    generator_face, generator_body, smplx_model, config = load_models(
-        './config/LS3DCG.json',
-        's2g_LS3DCG',
-        'experiments/2022-10-19-smplx_S2G-LS3DCG/ckpt-99.pth',
-        's2g_LS3DCG',
-        'experiments/2022-10-19-smplx_S2G-LS3DCG/ckpt-99.pth'
-    )
-    
-    # Initialize rendering tool
-    rendertool = RenderTool('visualise/video/' + config.Log.name)
-
-    # Inference
-    infer(generator_body, generator_face, smplx_model, rendertool, config, audio_file)
-
-    # Provide output (e.g., path to the rendered video)
-    output_video_path = f'visualise/video/{config.Log.name}/{audio_file.split("/")[-1].split(".")[0]}.npy'
-    return output_video_path
-
-# Gradio interface
-iface = gr.Interface(
-    fn=run_inference,
-    inputs=gr.inputs.Audio(source="upload", type="filepath", label="Upload Audio File"),
-    outputs=gr.outputs.Textbox(label="Output Video Path"),
-    title="Audio to 3D Model Renderer",
-    description="Upload an audio file to generate a 3D model rendering."
-)
-
-if __name__ == "__main__":
-    iface.launch()
+# Create a viewer
+pyrender.Viewer(scene, use_raymond_lights=True)