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Empty file modified .gitignore
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15 changes: 15 additions & 0 deletions .vscode/launch.json
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Expand Up @@ -12,6 +12,21 @@
"program": "${file}",
"console": "integratedTerminal",
"cwd" : "${fileDirname}", // run at the location of the runfile
// hook terminal cmd to debug file
"args": [
// "--gpu=0",
"--nr_types=6",
"--type_info_path=type_info.json",
"--batch_size=64",
"--model_mode=fast",
"--model_path=../../pretrained/hovernet_fast_pannuke_pytorch.tar",
"--nr_inference_workers=4",
"--nr_post_proc_workers=8",
"wsi",
"--ambiguous_size=328",
"--input_dir=exp_output/wsi/samples/",
"--output_dir=exp_output/wsi/pred/",
]
},
{
"name": "Python: Remote Attach",
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2 changes: 1 addition & 1 deletion convert_format.py
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Expand Up @@ -55,7 +55,7 @@ def rgb2int(rgb):
target_format = "qupath"
# to rescale the coordinate set to match with lv0 mag of the wsi
scale_factor = 1.0
root_dir = "dataset/dummy/out/"
root_dir = "exp_output/wsi/pred/"

# to define the name, and color conversion code for each target format
type_info_dict = {
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6 changes: 3 additions & 3 deletions infer/base.py
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Expand Up @@ -67,11 +67,11 @@ def __load_model(self):

net.load_state_dict(saved_state_dict, strict=True)
net = torch.nn.DataParallel(net)
net = net.to("cuda")
self.model = net.to("cuda")

module_lib = import_module("models.hovernet.run_desc")
run_step = getattr(module_lib, "infer_step")
self.run_step = lambda input_batch: run_step(input_batch, net)
self.run_step = getattr(module_lib, "infer_step")
# self.run_step = lambda input_batch: run_step(input_batch, net)

module_lib = import_module("models.hovernet.post_proc")
self.post_proc_func = getattr(module_lib, "process")
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