Gil-Simas commited on
Commit
d63b569
·
1 Parent(s): 4e6e22b
Files changed (1) hide show
  1. user-friendly-metrics.py +13 -20
user-friendly-metrics.py CHANGED
@@ -82,16 +82,14 @@ class UserFriendlyMetrics(evaluate.Metric):
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  citation=_CITATION,
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  inputs_description=_KWARGS_DESCRIPTION,
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  # This defines the format of each prediction and reference
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- features=datasets.Features(
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- {
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- "predictions": datasets.Sequence(
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- datasets.Sequence(datasets.Value("float"))
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- ),
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- "references": datasets.Sequence(
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- datasets.Sequence(datasets.Value("float"))
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- ),
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- }
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- ),
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  # Additional links to the codebase or references
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  codebase_urls=["http://github.com/path/to/codebase/of/new_module"],
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  reference_urls=["http://path.to.reference.url/new_module"],
@@ -155,7 +153,7 @@ class UserFriendlyMetrics(evaluate.Metric):
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  predictions, references = payload_to_uf_metrics(payload, model_name=model_name, filter_dict=self.filter_dict)
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- results[model_name]["per_sequence"][seq_name] = self._compute(predictions, references)
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  # overall
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  model_payload = Payload(
@@ -166,7 +164,7 @@ class UserFriendlyMetrics(evaluate.Metric):
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  )
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  predictions, references = payload_to_uf_metrics(payload, model_name=model_name, filter_dict=self.filter_dict)
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- results[model_name]["overall"] = self._compute(predictions, references)
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  return results
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@@ -220,19 +218,14 @@ class UserFriendlyMetrics(evaluate.Metric):
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  categories = {
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  "user_friendly_metrics": {
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- "mostly_tracked_score_0.3",
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- "mostly_tracked_score_0.5",
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- "mostly_tracked_score_0.8",
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  },
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  "evaluation_metrics_dev": {
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  "recall",
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  },
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  "user_friendly_metrics_dev": {
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- "mostly_tracked_count_0.3",
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- "mostly_tracked_count_0.5",
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- "mostly_tracked_count_0.8",
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- "unique_obj_count",
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- },
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  "predictions_summary": {
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  "tp",
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  "fn",
 
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  citation=_CITATION,
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  inputs_description=_KWARGS_DESCRIPTION,
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  # This defines the format of each prediction and reference
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+ features=datasets.Features({
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+ "predictions": datasets.Sequence(
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+ datasets.Sequence(datasets.Value("float"))
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+ ),
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+ "references": datasets.Features({ "all":
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+ datasets.Sequence(datasets.Sequence(datasets.Value("float")))}
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+ )
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+ }), #couldn't get this to work
 
 
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  # Additional links to the codebase or references
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  codebase_urls=["http://github.com/path/to/codebase/of/new_module"],
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  reference_urls=["http://path.to.reference.url/new_module"],
 
153
 
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  predictions, references = payload_to_uf_metrics(payload, model_name=model_name, filter_dict=self.filter_dict)
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+ results[model_name]["per_sequence"][seq_name] = self._compute(predictions=predictions, references=references)
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  # overall
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  model_payload = Payload(
 
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  )
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  predictions, references = payload_to_uf_metrics(payload, model_name=model_name, filter_dict=self.filter_dict)
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+ results[model_name]["overall"] = self._compute(predictions=predictions, references=references)
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  return results
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218
 
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  categories = {
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  "user_friendly_metrics": {
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+ f"mostly_tracked_score_{str(threshold).replace('.', '_')}" for threshold in self.recognition_thresholds
 
 
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  },
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  "evaluation_metrics_dev": {
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  "recall",
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  },
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  "user_friendly_metrics_dev": {
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+ f"mostly_tracked_count_{str(threshold).replace('.', '_')}" for threshold in self.recognition_thresholds
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+ }.union("unique_object_count"),
 
 
 
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  "predictions_summary": {
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  "tp",
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  "fn",