env

.gitignore

@@ -1,4 +1,5 @@
 outputs/
 ckpt/
 checkpoints/*
-__pycache__/
+__pycache__/
+env.txt

objctrl_2_5d/objctrl_2_5d.py

@@ -115,8 +115,6 @@ def run(pipeline, device):
         #### preparing mask
         
         mask = Image.fromarray(mask)
-        mask.save(f'{cur_OUTPUT_PATH}/org_mask_big.png')
-        mask = Image.open(f'{cur_OUTPUT_PATH}/org_mask_big.png')
         mask = mask.resize((W, H))
         mask = np.array(mask).astype(np.float32)
         mask = np.expand_dims(mask, axis=-1)

objctrl_2_5d/utils/ui_utils.py

@@ -190,7 +190,7 @@ def traj2cam(traj, depth, rescale):
     zc = []
     for i in range(num_frames):
         zc.append(r_depth[int(trajectory[i][1]), int(trajectory[i][0])])
-    print(f'zc: {zc}')
+    # print(f'zc: {zc}')
     
     ## norm zc
     zc_norm = np.array(zc)
@@ -202,8 +202,8 @@ def traj2cam(traj, depth, rescale):
     if zc_grad_std > zc_threshold:
         zc = [zc[0]] * num_frames
         
-    print(f'zc_grad_std: {zc_grad_std}, zc_threshold: {zc_threshold}')
-    print(f'zc: {zc}')
+    # print(f'zc_grad_std: {zc_grad_std}, zc_threshold: {zc_threshold}')
+    # print(f'zc: {zc}')
 
     traj_w2c = trajectory_to_camera_poses_v1(trajectory, intrinsics, num_frames, zc=zc) # numpy: [n_frame, 4, 4]
     RTs = traj_w2c[:, :3]

requirements.txt

@@ -16,4 +16,16 @@ safetensors
 triton
 termcolor==2.4.0
 gradio-image-prompter==0.1.0
-hydra-core==1.3.2
+hydra-core==1.3.2
+scipy
+plotly
+huggingface_hub==0.10.1
+iopath
+timm==0.6.13
+numpy==1.25.2
+accelerate==0.34.2
+pydantic==2.8.2
+starlette==0.37.2
+fastapi==0.111.1
+fastapi-cli==0.0.4
+av==13.0.0