How to generate the prompt for tracking anything?

``` python
import torch
from sam2.build_sam import build_sam2_video_predictor
from sam2.utils.amg import build_point_grid
import numpy as np
import os
import cv2
import rerun as rr
import time
import matplotlib.pyplot as plt

rr.init("tum_rgbd_sam2", spawn=True)

cmap = plt.get_cmap("tab10")

def show_anns(anns, img, idxs, borders=True):
if len(anns) == 0:
return

mask_img = np.zeros_like(img, dtype=np.float32)
h, w= img.shape[:2]
for ann, obj_id in zip(anns, idxs):
cmap_idx = 0 if obj_id is None else obj_id
color = np.array([*cmap(cmap_idx)[:3]])
m = ann.reshape(h, w, 1).cpu().numpy()
mask_img += m * color.reshape(1, 1, -1)
if borders:

contours, _ = cv2.findContours(m.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
# Try to smooth contours
contours = [cv2.approxPolyDP(contour, epsilon=0.01, closed=True) for contour in contours]
cv2.drawContours(mask_img, contours, -1, (0, 0, 1, 0.4), thickness=1)

img = np.hstack((img, (mask_img * 255).astype(np.uint8)))

rr.set_time_seconds("timestamp", time.time())
rr.log("image", rr.Image(img, rr.ColorModel.BGR))

sam2_checkpoint = "./checkpoints/sam2.1_hiera_tiny.pt"
model_cfg = "configs/sam2.1/sam2.1_hiera_t.yaml"

sam2 = build_sam2_video_predictor(model_cfg, sam2_checkpoint, device="cuda", apply_postprocessing=False)

images = sorted(os.listdir("/home/dapeng/data/TUM_RGBD/rgbd_dataset_freiburg1_desk/rgb"))

origin_image_size = (640, 480)
point_coords = build_point_grid(4)
point_coords = point_coords.reshape(-1, 1, 2) * np.array(origin_image_size).reshape(1, 1, 2)
point_labels = np.ones((point_coords.shape[0], 1), dtype=np.int32)

with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
state = sam2.init_state("/home/dapeng/data/TUM_RGBD/rgbd_dataset_freiburg1_desk/rgb")
for i in range(point_coords.shape[0]):
frame_idx, object_ids, masks = sam2.add_new_points_or_box(state, 0, i, points=point_coords[i], labels=point_labels[i])
for frame_idx, object_ids, masks in sam2.propagate_in_video(state):
for i in range(point_coords.shape[0]):
sam2.add_new_points_or_box(state, frame_idx, i, points=point_coords[i], labels=point_labels[i])
img = cv2.imread(os.path.join("/home/dapeng/data/TUM_RGBD/rgbd_dataset_freiburg1_desk/rgb", images[frame_idx]), cv2.IMREAD_COLOR)
show_anns(masks > 0.0, img, object_ids)
```

https://github.com/user-attachments/assets/89f4b3ea-a850-4c7a-ae45-9e045012b2b4