Update webui

Author: billl-jiang

README.md

@@ -17,18 +17,12 @@
 
 </div>
 
-
-
 <div align="center">
 
-
 https://github.com/OpenMotionLab/MotionGPT/assets/120085716/a741e162-b2f4-4f65-af8e-aa19c4115a9e
 
 https://github.com/OpenMotionLab/MotionGPT/assets/120085716/5b60aebc-ce80-42e8-8a4c-1f673e85b84e
 
-
-
-
 <!-- <img src="https://cdn.discordapp.com/attachments/941582479117127680/1111543600879259749/20230526075532.png" width="350px"> -->
 </div>
 
@@ -223,7 +217,7 @@ YOUR_BLENDER_PYTHON_PATH/python -m pip install -r prepare/requirements_render.tx
 Run the following command using blender:
 
 ```
-YOUR_BLENDER_PATH/blender --background --python render.py -- --cfg=./configs/render.yaml --dir=YOUR_NPY_FOLDER --mode=video --joint_type=HumanML3D
+YOUR_BLENDER_PATH/blender --background --python render.py -- --cfg=./configs/render.yaml --dir=YOUR_NPY_FOLDER --mode=video
 ```
 
 ### 2. Create SMPL meshes with:
@@ -242,7 +236,7 @@ This outputs:
 Run the following command to render SMPL using blender:
 
 ```
-YOUR_BLENDER_PATH/blender --background --python render.py -- --cfg=./configs/render.yaml --dir=YOUR_NPY_FOLDER --mode=video --joint_type=HumanML3D
+YOUR_BLENDER_PATH/blender --background --python render.py -- --cfg=./configs/render.yaml --dir=YOUR_NPY_FOLDER --mode=video
 ```
 
 optional parameters:

app.py

@@ -32,7 +32,7 @@ def render(execute_python, npy_path, jointtype, cfg_path):
     export_scripts = "render.py"
 
     os.system(
-        f"{execute_python} --background --python {export_scripts} -- --cfg={cfg_path} --npy={npy_path} --joint_type={jointtype}"
+        f"{execute_python} --background --python {export_scripts} -- --cfg={cfg_path} --npy={npy_path}"
     )
 
     fig_path = Path(str(npy_path).replace(".npy", ".png"))

mGPT/utils/demo_utils.py

@@ -447,7 +447,7 @@ def estimate_translation(S, joints_2d, focal_length=5000., img_size=224.):
     joints_2d = joints_2d[:, 25:, :].cpu().numpy()
     joints_conf = joints_2d[:, :, -1]
     joints_2d = joints_2d[:, :, :-1]
-    trans = np.zeros((S.shape[0], 3), dtype=np.float6432)
+    trans = np.zeros((S.shape[0], 3), dtype=np.float32)
     # Find the translation for each example in the batch
     for i in range(S.shape[0]):
         S_i = S[i]

mGPT/utils/geometry_conver.py

@@ -35,24 +35,26 @@
   min-height: 500px;
 }
 
+[class*='message-buttons'] {
+  visibility: hidden;
+}
+
 [class*='message'] {
-  border-radius: var(--radius-xl) !important;
   border: none;
-  padding: var(--spacing-xl) !important;
-  font-size: var(--text-xl) !important;
-  line-height: var(--line-lg) !important;
-  min-height: calc(var(--text-lg) * var(--line-lg) + 2 * var(--spacing-xl));
-  min-width: calc(var(--text-lg) * var(--line-lg) + 2 * var(--spacing-xl));
+  border-radius: var(--radius-xl) !important;
+  /* font-size: var(--text-xl) !important;
+  line-height: var(--line-xl) !important; */
 }
+
 [data-testid='bot'] {
-  max-width: 85%;
+  max-width: 70%;
   width: auto !important;
-  border-bottom-left-radius: 0 !important;
+  /* border-bottom-left-radius: 0 !important; */
 }
 [data-testid='user'] {
-  max-width: 85%;
+  max-width: 70%;
   width: auto !important;
-  border-bottom-right-radius: 0 !important;
+  /* border-bottom-right-radius: 0 !important; */
 }
 
 /* Text & Video */
@@ -64,22 +66,7 @@
   max-width: 340px;
 }
 
-@media only screen and (min-width: 768px) {
-  .side-content {
-    float: left;
-    overflow-wrap: break-word;
-    padding-right: 2rem;
-  }
-
-  .side-video {
-    float: right;
-  }
-}
-
 /* Buttom */
-#upload {
-  color: #000000;
-}
 
 .videodl-button {
   position: absolute;

public/css/custom.css

@@ -1,5 +1,5 @@
 # parallel render
-for i in `seq 0 4`
+for i in `seq 0 7`
 do
     for j in `seq 0 1`
     do

scripts/fit_motion_parallel.sh

@@ -9,15 +9,18 @@
 from mGPT.models.build_model import build_model
 from mGPT.utils.load_checkpoint import load_pretrained, load_pretrained_vae
 
+
 def main():
 
     # parse options
     cfg = parse_args(phase="test")  # parse config file
     cfg.TRAIN.STAGE = "token"
     cfg.TRAIN.BATCH_SIZE = 1
-    
+
     model_name = cfg.model.target.split('.')[-2].lower()
-    output_dir = Path(os.path.join(cfg.FOLDER, model_name, cfg.NAME, "tokens_visual_" + cfg.TIME))
+    output_dir = Path(
+        os.path.join(cfg.FOLDER, model_name, cfg.NAME,
+                     "tokens_visual_" + cfg.TIME))
 
     # set seed
     pl.seed_everything(cfg.SEED_VALUE)
@@ -44,39 +47,38 @@ def main():
     # loading state dict
     if cfg.TEST.CHECKPOINTS:
         load_pretrained(cfg, model, phase="test")
-        
+
     if cfg.ACCELERATOR == "gpu":
         model = model.cuda()
-        
+
     model.eval()
     codes = cfg.model.params.codebook_size
     with torch.no_grad():
         for i in tqdm(range(codes)):
-            
+
             # Generate motion from token
             m_token = torch.LongTensor(1, 1).fill_(i).to(model.device)
             # vq_latent = model.vae.quantizer.dequantize(m_token)
             gen_motion = model.vae.decode(m_token)
             gen_motion = model.feats2joints(gen_motion).to('cpu').numpy()
-            
+
             # Generate translation from token
-            texts = [f'Generate text: <motion_id_{codes}><motion_id_{i}><motion_id_{codes +1}>']
+            texts = [
+                f'Generate text: <motion_id_{codes}><motion_id_{i}><motion_id_{codes +1}>'
+            ]
             # texts = [f'Use only one word to describe: <motion_id_{codes}><motion_id_{i}><motion_id_{codes +1}>']
-            batch = {
-                "text": texts,
-                "length": [0]
-            }
-            
-            out_text = model(batch)['texts']
-            print(out_text)
-            out_text_path = os.path.join(output_dir, f'{i}.txt')
-            Path(out_text_path).parent.mkdir(parents=True, exist_ok=True)
-            with open(out_text_path, 'w') as f:
-                f.write(out_text[0])
-            
+            batch = {"text": texts, "length": [0]}
+
+            # out_text = model(batch)['texts']
+            # print(out_text)
+            # out_text_path = os.path.join(output_dir, f'{i}.txt')
+            # Path(out_text_path).parent.mkdir(parents=True, exist_ok=True)
+            # with open(out_text_path, 'w') as f:
+            #     f.write(out_text[0])
+
             target_path = os.path.join(output_dir, f'{i}.npy')
             Path(target_path).parent.mkdir(parents=True, exist_ok=True)
-            
+
             np.save(target_path, gen_motion)
 
     print(