riaz.somc/transformers
1
0
Fork 0
mirror of https://github.com/huggingface/transformers.git synced 2025-07-04 13:20:12 +06:00
Code Issues Actions 21 Packages Projects Releases Wiki Activity

[SAM-HQ] Update names in the docs (#38058)

Browse Source 
Update names
This commit is contained in:
NielsRogge 2025-05-19 18:21:14 +02:00 committed by GitHub
parent 04282a9ef5
commit 7c9b0ca08c
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 32 additions and 32 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
docs/source/en/model_doc/sam_hq.md
View File

@ -43,8 +43,8 @@ import requests
from transformers import SamHQModel, SamHQProcessor from transformers import SamHQModel, SamHQProcessor
device = "cuda" if torch.cuda.is_available() else "cpu" device = "cuda" if torch.cuda.is_available() else "cpu"
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b").to(device) model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base").to(device)
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
img_url = "https://huggingface.co/ybelkada/segment-anything/resolve/main/assets/car.png" img_url = "https://huggingface.co/ybelkada/segment-anything/resolve/main/assets/car.png"
raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB") raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB")
@ -69,8 +69,8 @@ import requests
from transformers import SamHQModel, SamHQProcessor from transformers import SamHQModel, SamHQProcessor
device = "cuda" if torch.cuda.is_available() else "cpu" device = "cuda" if torch.cuda.is_available() else "cpu"
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b").to(device) model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base").to(device)
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
img_url = "https://huggingface.co/ybelkada/segment-anything/resolve/main/assets/car.png" img_url = "https://huggingface.co/ybelkada/segment-anything/resolve/main/assets/car.png"
raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB") raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB")

56
tests/models/sam_hq/test_modeling_sam_hq.py
View File

@ -715,7 +715,7 @@ class SamHQModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
model_name = "sushmanth/sam_hq_vit_b" model_name = "syscv-community/sam-hq-vit-base"
model = SamHQModel.from_pretrained(model_name) model = SamHQModel.from_pretrained(model_name)
self.assertIsNotNone(model) self.assertIsNotNone(model)
@ -801,8 +801,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
cleanup(torch_device, gc_collect=True) cleanup(torch_device, gc_collect=True)
def test_inference_mask_generation_no_point(self): def test_inference_mask_generation_no_point(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -821,8 +821,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
) )
def test_inference_mask_generation_one_point_one_bb(self): def test_inference_mask_generation_one_point_one_bb(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -845,8 +845,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
) )
def test_inference_mask_generation_batched_points_batched_images(self): def test_inference_mask_generation_batched_points_batched_images(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -887,8 +887,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(masks, EXPECTED_MASKS, atol=9e-3)) self.assertTrue(torch.allclose(masks, EXPECTED_MASKS, atol=9e-3))
def test_inference_mask_generation_one_point_one_bb_zero(self): def test_inference_mask_generation_one_point_one_bb_zero(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -913,8 +913,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8680), atol=1e-3)) self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8680), atol=1e-3))
def test_inference_mask_generation_with_labels(self): def test_inference_mask_generation_with_labels(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -933,8 +933,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.9137), atol=1e-4)) self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.9137), atol=1e-4))
def test_inference_mask_generation_without_labels(self): def test_inference_mask_generation_without_labels(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -950,8 +950,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.9137), atol=1e-3)) self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.9137), atol=1e-3))
def test_inference_mask_generation_two_points_with_labels(self): def test_inference_mask_generation_two_points_with_labels(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -970,8 +970,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8859), atol=1e-3)) self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8859), atol=1e-3))
def test_inference_mask_generation_two_points_without_labels(self): def test_inference_mask_generation_two_points_without_labels(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -987,8 +987,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8859), atol=1e-3)) self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8859), atol=1e-3))
def test_inference_mask_generation_two_points_batched(self): def test_inference_mask_generation_two_points_batched(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -1013,8 +1013,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(scores[1][-1], torch.tensor(0.4482), atol=1e-4)) self.assertTrue(torch.allclose(scores[1][-1], torch.tensor(0.4482), atol=1e-4))
def test_inference_mask_generation_one_box(self): def test_inference_mask_generation_one_box(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -1031,8 +1031,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.6265), atol=1e-4)) self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.6265), atol=1e-4))
def test_inference_mask_generation_batched_image_one_point(self): def test_inference_mask_generation_batched_image_one_point(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -1060,8 +1060,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
self.assertTrue(torch.allclose(scores_batched[1, :], scores_single, atol=1e-4)) self.assertTrue(torch.allclose(scores_batched[1, :], scores_single, atol=1e-4))
def test_inference_mask_generation_two_points_point_batch(self): def test_inference_mask_generation_two_points_point_batch(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -1084,8 +1084,8 @@ class SamHQModelIntegrationTest(unittest.TestCase):
) )
def test_inference_mask_generation_three_boxes_point_batch(self): def test_inference_mask_generation_three_boxes_point_batch(self):
model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base")
processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base")
model.to(torch_device) model.to(torch_device)
model.eval() model.eval()
@ -1110,7 +1110,7 @@ class SamHQModelIntegrationTest(unittest.TestCase):
torch.testing.assert_close(iou_scores, EXPECTED_IOU, atol=1e-4, rtol=1e-4) torch.testing.assert_close(iou_scores, EXPECTED_IOU, atol=1e-4, rtol=1e-4)
def test_dummy_pipeline_generation(self): def test_dummy_pipeline_generation(self):
generator = pipeline("mask-generation", model="sushmanth/sam_hq_vit_b", device=torch_device) generator = pipeline("mask-generation", model="syscv-community/sam-hq-vit-base", device=torch_device)
raw_image = prepare_image() raw_image = prepare_image()
_ = generator(raw_image, points_per_batch=64) _ = generator(raw_image, points_per_batch=64)