SAM V1,V2,V3
Collection
7 items • Updated
How to use kerasformers/sam2_hiera_base_plus with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
How to use kerasformers/sam2_hiera_base_plus with Keras:
# Available backend options are: "jax", "torch", "tensorflow".
import os
os.environ["KERAS_BACKEND"] = "jax"
import keras
model = keras.saving.load_model("hf://kerasformers/sam2_hiera_base_plus")
How to use kerasformers/sam2_hiera_base_plus with sam2:
# Use SAM2 with images
import torch
from sam2.sam2_image_predictor import SAM2ImagePredictor
predictor = SAM2ImagePredictor.from_pretrained(kerasformers/sam2_hiera_base_plus)
with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
predictor.set_image(<your_image>)
masks, _, _ = predictor.predict(<input_prompts>) # Use SAM2 with videos
import torch
from sam2.sam2_video_predictor import SAM2VideoPredictor
predictor = SAM2VideoPredictor.from_pretrained(kerasformers/sam2_hiera_base_plus)
with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
state = predictor.init_state(<your_video>)
# add new prompts and instantly get the output on the same frame
frame_idx, object_ids, masks = predictor.add_new_points(state, <your_prompts>):
# propagate the prompts to get masklets throughout the video
for frame_idx, object_ids, masks in predictor.propagate_in_video(state):
...Pure-Keras 3 weights for kerasformers, mirrored from the source. License: apache-2.0.
from kerasformers.models.sam2 import SAM2PromptableSegment
model = SAM2PromptableSegment.from_weights("sam2_hiera_base_plus")