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inference.py

@@ -1,12 +1,12 @@
 """
-Inference script for SPECIESNET-v4-0-1-A-v1 (SpeciesNet classifier)
+Inference script for SPECIESNET-v4-0-2-A (SpeciesNet classifier)
 
 SpeciesNet is an image classifier designed to accelerate the review of images
 from camera traps. Trained at Google using a large dataset of camera trap images
 and an EfficientNet V2 M architecture. Classifies images into one of 2,498 labels
 covering diverse animal species, higher-level taxa, and non-animal classes.
 
-Model: SpeciesNet v4.0.1a (always_crop variant)
+Model: SpeciesNet v4.0.2a (always_crop variant)
 Input: 480x480 RGB images (NHWC layout)
 Framework: PyTorch (torch.fx GraphModule)
 Classes: 2,498
@@ -36,8 +36,8 @@ ImageFile.LOAD_TRUNCATED_IMAGES = True
 if platform.system() != "Windows":
     pathlib.WindowsPath = pathlib.PosixPath
 
-# Hardcoded model parameters for SpeciesNet v4.0.1a
-LABELS_FILENAME = "always_crop_99710272_22x8_v12_epoch_00148.labels.txt"
+# Hardcoded model parameters for SpeciesNet v4.0.2a
+LABELS_FILENAME = "always_crop_99710272_22x8_v12_epoch_00148.labels.20251208.txt"
 IMG_SIZE = 480