commit

app.py

@@ -54,15 +54,15 @@ def process(inputfiles, input_path='demo'):
     imgs_path = temp_dir
     output_path = f'./results/{input_path}/output'
     rearranged_path = f'{output_path}_rearranged'
-    cmd(f"python dynamic_predictor/launch.py --mode=eval_pose_custom \
-        --pretrained=Kai422kx/das3r \
-        --dir_path={imgs_path} \
-        --output_dir={output_path} \
-        --use_pred_mask ")
-    # dynamic_predictor_main(pretrained='Kai422kx/das3r', dir_path=imgs_path, output_dir=output_path, use_pred_mask=True, n_iter=150)
-    # rearrange_main(output_dir=output_path, rearranged_path = rearranged_path)
-    # train_main(s = rearranged_path, m = rearranged_path, iter = 2000)
-    # render_main(s = rearranged_path, m = rearranged_path, iter = 2000, get_video = True)
+    # cmd(f"python dynamic_predictor/launch.py --mode=eval_pose_custom \
+    #     --pretrained=Kai422kx/das3r \
+    #     --dir_path={imgs_path} \
+    #     --output_dir={output_path} \
+    #     --use_pred_mask ")
+    dynamic_predictor_main(pretrained='Kai422kx/das3r', dir_path=imgs_path, output_dir=output_path, use_pred_mask=True, n_iter=150)
+    rearrange_main(output_dir=output_path, rearranged_path = rearranged_path)
+    train_main(s = rearranged_path, m = rearranged_path, iter = 2000)
+    render_main(s = rearranged_path, m = rearranged_path, iter = 2000, get_video = True)