Unverified Commit ce87dca1 authored by NielsRogge's avatar NielsRogge Committed by GitHub
Browse files

[Object detection pipeline] Lower threshold (#30710)

* Lower threshold

* Address comment
parent 69d9bca5
...@@ -83,7 +83,7 @@ class ObjectDetectionPipeline(Pipeline): ...@@ -83,7 +83,7 @@ class ObjectDetectionPipeline(Pipeline):
The pipeline accepts either a single image or a batch of images. Images in a batch must all be in the The pipeline accepts either a single image or a batch of images. Images in a batch must all be in the
same format: all as HTTP(S) links, all as local paths, or all as PIL images. same format: all as HTTP(S) links, all as local paths, or all as PIL images.
threshold (`float`, *optional*, defaults to 0.9): threshold (`float`, *optional*, defaults to 0.5):
The probability necessary to make a prediction. The probability necessary to make a prediction.
timeout (`float`, *optional*, defaults to None): timeout (`float`, *optional*, defaults to None):
The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and
...@@ -120,7 +120,7 @@ class ObjectDetectionPipeline(Pipeline): ...@@ -120,7 +120,7 @@ class ObjectDetectionPipeline(Pipeline):
model_outputs["bbox"] = model_inputs["bbox"] model_outputs["bbox"] = model_inputs["bbox"]
return model_outputs return model_outputs
def postprocess(self, model_outputs, threshold=0.9): def postprocess(self, model_outputs, threshold=0.5):
target_size = model_outputs["target_size"] target_size = model_outputs["target_size"]
if self.tokenizer is not None: if self.tokenizer is not None:
# This is a LayoutLMForTokenClassification variant. # This is a LayoutLMForTokenClassification variant.
......
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