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Update README.md

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@@ -73,15 +73,13 @@ To encourage development of better machine learning methods for operating with d
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  ## Splits
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  - Training Set:
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  - Full Training Set: 1,755,602 observations, 3,307,025 images
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- - Labeled Training Sets:
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  - 20%: 334,383 observations, 390,908 images
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  - 5%: 93,708 observations, 97,727 images
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  - 1%: 19,371 observations, 19,545 images
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  - 0.25%: 4,878 observations, 4,886 images
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- - Validation Set:
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- - 150,555 observations, 279,114 images
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- - Test Set:
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- - 182,618 observations, 334,887 images
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  ## Acquisition
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  - Ground-Level Images:
@@ -103,7 +101,7 @@ To encourage development of better machine learning methods for operating with d
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  - observation_uuid (string): Unique identifier for each observation in the dataset.
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  - latitude (float32): Latitude coordinate of the observation.
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  - longitude (float32): Longitude coordinate of the observation.
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- - positional_accuracy (int64): Accuracy of the geographical position, measured in meters.
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  - taxon_id (int64): Identifier for the taxonomic classification of the observed species.
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  - quality_grade (string): Quality grade of the observation, indicating its verification status (e.g., research-grade, needs ID).
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  - gl_image_date (string): Date when the ground-level image was taken.
 
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  ## Splits
74
  - Training Set:
75
  - Full Training Set: 1,755,602 observations, 3,307,025 images
76
+ - Labeled Training Set:
77
  - 20%: 334,383 observations, 390,908 images
78
  - 5%: 93,708 observations, 97,727 images
79
  - 1%: 19,371 observations, 19,545 images
80
  - 0.25%: 4,878 observations, 4,886 images
81
+ - Validation Set: 150,555 observations, 279,114 images
82
+ - Test Set: 182,618 observations, 334,887 images
 
 
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  ## Acquisition
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  - Ground-Level Images:
 
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  - observation_uuid (string): Unique identifier for each observation in the dataset.
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  - latitude (float32): Latitude coordinate of the observation.
103
  - longitude (float32): Longitude coordinate of the observation.
104
+ - positional_accuracy (int64): Accuracy of the geographical position.
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  - taxon_id (int64): Identifier for the taxonomic classification of the observed species.
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  - quality_grade (string): Quality grade of the observation, indicating its verification status (e.g., research-grade, needs ID).
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  - gl_image_date (string): Date when the ground-level image was taken.