init project

app.py

@@ -299,7 +299,7 @@ def get_mask_from_img_sam1(mobilesamv2, yolov8, sam1_image, yolov8_image, origin
     return ret_mask
 
 @torch.no_grad
-def get_cog_feats(images, pe3r, device):
+def get_cog_feats(images, device):
     cog_seg_maps = []
     rev_cog_seg_maps = []
     inference_state = pe3r.sam2.init_state(images=images.sam2_images, video_height=images.sam2_video_size[0], video_width=images.sam2_video_size[1])
@@ -435,7 +435,7 @@ def get_cog_feats(images, pe3r, device):
     return cog_seg_maps, rev_cog_seg_maps, multi_view_clip_feats
 
 @spaces.GPU(duration=180)
-def get_reconstructed_scene(outdir, pe3r, device, silent, filelist, schedule, niter, min_conf_thr,
+def get_reconstructed_scene(outdir, device, silent, filelist, schedule, niter, min_conf_thr,
                             as_pointcloud, mask_sky, clean_depth, transparent_cams, cam_size,
                             scenegraph_type, winsize, refid):
     """
@@ -448,8 +448,8 @@ def get_reconstructed_scene(outdir, pe3r, device, silent, filelist, schedule, ni
     images = Images(filelist=filelist, device=device)
     
     # try:
-    cog_seg_maps, rev_cog_seg_maps, cog_feats = get_cog_feats(images, pe3r, device)
-    imgs = load_images(images, rev_cog_seg_maps, size=512, verbose=not silent)
+    cog_seg_maps, rev_cog_seg_maps, cog_feats = get_cog_feats(images, device)
+    # imgs = load_images(images, rev_cog_seg_maps, size=512, verbose=not silent)
     # except Exception as e:
         # rev_cog_seg_maps = []
         # for tmp_img in images.np_images: