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README.md

@@ -40,9 +40,9 @@ Tips:
 
 - A list of all objects with the names you gave them will be displayed in a tree view on the left side of the screen, where you can toggle them. F-strings are recommended for automatically generating object names
 - Use "/" inside names for example `image/0` to create nested trees.
-- For convenience, we accept numpy arrays, torch Tensors, and lists in general for any arguments marked at `np.ndarray`  (by default torch is not imported to avoid having it as a dependency). 
+- For convenience, we accept numpy arrays, torch Tensors, and lists in general for any arguments marked at `np.ndarray`  (by default torch is not imported to avoid having it as a dependency).
 - The initial camera pose will be automatically determined. Pass `center=[x, y, z]` (camera position) ,
-    `origin=[x,y,z]` (camera target), `forward=[x,y,z]` (forward vector), `world_up=[x,y,z]` (world space up vector) to display() or export() or embed() to manually set an initial pose. 
+    `origin=[x,y,z]` (camera target), `forward=[x,y,z]` (forward vector), `world_up=[x,y,z]` (world space up vector) to display() or export() or embed() to manually set an initial pose.
     A convenience function `scene.set_opencv()` is given to set the world up axis to `-y` (this also changes the default behavior of `add_image`).
 - Use `scene.export("path")` to manually generate a directory you can open in the browser or upload somewhere
 
@@ -101,7 +101,7 @@ from nerfvis import scene
 import numpy as np
 
 # Set -y up world, and also flips the image
-scene.set_opencv() 
+scene.set_opencv()
 
 # Example data
 f = 1111.0
@@ -123,10 +123,12 @@ scene.add_camera_frustum("cameras", r=c2ws[:, :3, :3], t=c2ws[:, :3, 3], focal_l
 for i in range(len(c2ws)):
     scene.add_image(
                   f"images/i",
-                  images[i],
+                  images[i], # Can be path too
                   r=c2ws[i, :3, :3], t=c2ws[i, :3, 3],
                   focal_length=f,
                   z=0.5,
+                  # NOTE: this image size is the display image size not original imge size
+                  # (that will be taken from the image). Keep it low if you are adding many images
                   image_size=64)
 scene.add_axes()
 scene.display()
@@ -167,7 +169,7 @@ right now. You may programmatically generate this. They will show up in the *lay
 Please also `pip install torch svox tqdm scipy` for adding NeRF (`set_nerf`)
 or `pip install trimesh` for using `add_mesh_from_file(path)`.
 
-To add cameras (also used for scaling scene, initializing camera etc), use 
+To add cameras (also used for scaling scene, initializing camera etc), use
 `add_camera_frustum(focal_length=.., image_width=.., image_height=.., z=..,  r=.., t=..)`
 
 ## Viewer Controls