Spaces:
Sleeping
Sleeping
local test
Browse files
app.py
CHANGED
@@ -35,14 +35,14 @@ glip_demo = GLIPDemo(
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show_mask_heatmaps=False
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)
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config_file = "configs/pretrain_new/
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weight_file = "MODEL/
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from copy import deepcopy
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cfg = deepcopy(cfg)
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cfg.merge_from_file(config_file)
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cfg.merge_from_list(["MODEL.WEIGHT", weight_file])
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cfg.merge_from_list(["MODEL.DEVICE", "cuda"])
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-
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cfg,
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min_image_size=800,
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confidence_threshold=0.7,
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@@ -50,27 +50,27 @@ fiber_demo = GLIPDemo(
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)
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config_file = "configs/pretrain_new/desco_glip.yaml"
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weight_file = "MODEL/
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from copy import deepcopy
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cfg = deepcopy(cfg)
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cfg.merge_from_file(config_file)
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cfg.merge_from_list(["MODEL.WEIGHT", weight_file])
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cfg.merge_from_list(["MODEL.DEVICE", "cuda"])
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-
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cfg,
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min_image_size=800,
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confidence_threshold=0.7,
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show_mask_heatmaps=False
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)
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config_file = "configs/pretrain_new/
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weight_file = "MODEL/
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from copy import deepcopy
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cfg = deepcopy(cfg)
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cfg.merge_from_file(config_file)
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cfg.merge_from_list(["MODEL.WEIGHT", weight_file])
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cfg.merge_from_list(["MODEL.DEVICE", "cuda"])
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-
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cfg,
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min_image_size=800,
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confidence_threshold=0.7,
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@@ -97,7 +97,7 @@ def predict(image, text, ground_tokens=""):
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fiber_result, _ = fiber_demo.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens, **athetics_params)
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local_result1, _ = local_demo1.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens, **athetics_params)
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local_result2, _ = local_demo2.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens, **athetics_params)
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return result[:, :, [2, 1, 0]], fiber_result[:, :, [2, 1, 0]], local_result1, local_result2
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image = gr.inputs.Image()
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show_mask_heatmaps=False
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)
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+
config_file = "configs/pretrain_new/desco_glip.yaml"
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weight_file = "MODEL/local1.pth"
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from copy import deepcopy
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cfg = deepcopy(cfg)
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cfg.merge_from_file(config_file)
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cfg.merge_from_list(["MODEL.WEIGHT", weight_file])
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cfg.merge_from_list(["MODEL.DEVICE", "cuda"])
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local_demo1 = GLIPDemo(
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cfg,
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min_image_size=800,
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confidence_threshold=0.7,
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)
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config_file = "configs/pretrain_new/desco_glip.yaml"
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weight_file = "MODEL/local2.pth"
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from copy import deepcopy
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cfg = deepcopy(cfg)
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cfg.merge_from_file(config_file)
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cfg.merge_from_list(["MODEL.WEIGHT", weight_file])
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cfg.merge_from_list(["MODEL.DEVICE", "cuda"])
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local_demo2 = GLIPDemo(
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cfg,
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min_image_size=800,
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confidence_threshold=0.7,
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show_mask_heatmaps=False
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)
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config_file = "configs/pretrain_new/desco_fiber.yaml"
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weight_file = "MODEL/desco_fiber_base.pth"
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from copy import deepcopy
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cfg = deepcopy(cfg)
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cfg.merge_from_file(config_file)
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cfg.merge_from_list(["MODEL.WEIGHT", weight_file])
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cfg.merge_from_list(["MODEL.DEVICE", "cuda"])
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fiber_demo = GLIPDemo(
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cfg,
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min_image_size=800,
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confidence_threshold=0.7,
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fiber_result, _ = fiber_demo.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens, **athetics_params)
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local_result1, _ = local_demo1.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens, **athetics_params)
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local_result2, _ = local_demo2.run_on_web_image(deepcopy(image[:, :, [2, 1, 0]]), text, 0.5, ground_tokens, **athetics_params)
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return result[:, :, [2, 1, 0]], fiber_result[:, :, [2, 1, 0]], local_result1[:, :, [2, 1, 0]], local_result2[:, :, [2, 1, 0]]
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image = gr.inputs.Image()
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