Update app.py

app.py

@@ -30,20 +30,11 @@ example_outputs_1 = [
     gr.Video(value=os.path.join(os.path.dirname(__file__), 'example/flamethrower,_with_fire,_scifi,_cyberpunk,_photorealistic,_8K,_HD.mp4'), autoplay=True)
 ]
 
-from shap_e.diffusion.sample import sample_latents
-from shap_e.diffusion.gaussian_diffusion import diffusion_from_config as diffusion_from_config_shape
-from shap_e.models.download import load_model, load_config
-from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget
-from shap_e.util.notebooks import decode_latent_mesh
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-xm = load_model('transmitter', device=device)
-model = load_model('text300M', device=device)
-# model.load_state_dict(torch.load('./load/shapE_finetuned_with_330kdata.pth', map_location=device)['model_state_dict'])
-diffusion = diffusion_from_config_shape(load_config('diffusion'))
 
-del xm
-del model
-del diffusion
+subprocess.run([
+                f'python shape.py'],
+            shell=True)
+
 def main(prompt, iteration,CFG, seed):
     if [prompt] in example_inputs:
         return example_outputs_1[example_inputs.index([prompt])]