From 7c9b0ca08cc45bcc4bfa48e802adc2d33b0bbb33 Mon Sep 17 00:00:00 2001 From: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Date: Mon, 19 May 2025 18:21:14 +0200 Subject: [PATCH] [SAM-HQ] Update names in the docs (#38058) Update names --- docs/source/en/model_doc/sam_hq.md | 8 +-- tests/models/sam_hq/test_modeling_sam_hq.py | 56 ++++++++++----------- 2 files changed, 32 insertions(+), 32 deletions(-) diff --git a/docs/source/en/model_doc/sam_hq.md b/docs/source/en/model_doc/sam_hq.md index 8c60b86117f..32181c4b873 100644 --- a/docs/source/en/model_doc/sam_hq.md +++ b/docs/source/en/model_doc/sam_hq.md @@ -43,8 +43,8 @@ import requests from transformers import SamHQModel, SamHQProcessor device = "cuda" if torch.cuda.is_available() else "cpu" -model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b").to(device) -processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") +model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base").to(device) +processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") 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") @@ -69,8 +69,8 @@ import requests from transformers import SamHQModel, SamHQProcessor device = "cuda" if torch.cuda.is_available() else "cpu" -model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b").to(device) -processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") +model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base").to(device) +processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") 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") diff --git a/tests/models/sam_hq/test_modeling_sam_hq.py b/tests/models/sam_hq/test_modeling_sam_hq.py index fa5a2a78bc3..502da82a277 100644 --- a/tests/models/sam_hq/test_modeling_sam_hq.py +++ b/tests/models/sam_hq/test_modeling_sam_hq.py @@ -715,7 +715,7 @@ class SamHQModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase): @slow 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) self.assertIsNotNone(model) @@ -801,8 +801,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): cleanup(torch_device, gc_collect=True) def test_inference_mask_generation_no_point(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -821,8 +821,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): ) def test_inference_mask_generation_one_point_one_bb(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -845,8 +845,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): ) def test_inference_mask_generation_batched_points_batched_images(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -887,8 +887,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(masks, EXPECTED_MASKS, atol=9e-3)) def test_inference_mask_generation_one_point_one_bb_zero(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -913,8 +913,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8680), atol=1e-3)) def test_inference_mask_generation_with_labels(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -933,8 +933,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.9137), atol=1e-4)) def test_inference_mask_generation_without_labels(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -950,8 +950,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.9137), atol=1e-3)) def test_inference_mask_generation_two_points_with_labels(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -970,8 +970,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8859), atol=1e-3)) def test_inference_mask_generation_two_points_without_labels(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -987,8 +987,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.8859), atol=1e-3)) def test_inference_mask_generation_two_points_batched(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -1013,8 +1013,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(scores[1][-1], torch.tensor(0.4482), atol=1e-4)) def test_inference_mask_generation_one_box(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -1031,8 +1031,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(scores[-1], torch.tensor(0.6265), atol=1e-4)) def test_inference_mask_generation_batched_image_one_point(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -1060,8 +1060,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): self.assertTrue(torch.allclose(scores_batched[1, :], scores_single, atol=1e-4)) def test_inference_mask_generation_two_points_point_batch(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -1084,8 +1084,8 @@ class SamHQModelIntegrationTest(unittest.TestCase): ) def test_inference_mask_generation_three_boxes_point_batch(self): - model = SamHQModel.from_pretrained("sushmanth/sam_hq_vit_b") - processor = SamHQProcessor.from_pretrained("sushmanth/sam_hq_vit_b") + model = SamHQModel.from_pretrained("syscv-community/sam-hq-vit-base") + processor = SamHQProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model.to(torch_device) model.eval() @@ -1110,7 +1110,7 @@ class SamHQModelIntegrationTest(unittest.TestCase): torch.testing.assert_close(iou_scores, EXPECTED_IOU, atol=1e-4, rtol=1e-4) 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() _ = generator(raw_image, points_per_batch=64)