Remove unnecessary architectures from image classifier ModelSpec

PiperOrigin-RevId: 481974529

mediapipe/model_maker/python/vision/image_classifier/model_spec.py

@@ -48,11 +48,6 @@ mobilenet_v2_spec = functools.partial(
     uri='https://tfhub.dev/google/tf2-preview/mobilenet_v2/feature_vector/4',
     name='mobilenet_v2')
 
-resnet_50_spec = functools.partial(
-    ModelSpec,
-    uri='https://tfhub.dev/google/imagenet/resnet_v2_50/feature_vector/4',
-    name='resnet_50')
-
 efficientnet_lite0_spec = functools.partial(
     ModelSpec,
     uri='https://tfhub.dev/tensorflow/efficientnet/lite0/feature-vector/2',
@@ -64,36 +59,14 @@ efficientnet_lite1_spec = functools.partial(
     input_image_shape=[240, 240],
     name='efficientnet_lite1')
 
-efficientnet_lite2_spec = functools.partial(
-    ModelSpec,
-    uri='https://tfhub.dev/tensorflow/efficientnet/lite2/feature-vector/2',
-    input_image_shape=[260, 260],
-    name='efficientnet_lite2')
-
-efficientnet_lite3_spec = functools.partial(
-    ModelSpec,
-    uri='https://tfhub.dev/tensorflow/efficientnet/lite3/feature-vector/2',
-    input_image_shape=[280, 280],
-    name='efficientnet_lite3')
-
-efficientnet_lite4_spec = functools.partial(
-    ModelSpec,
-    uri='https://tfhub.dev/tensorflow/efficientnet/lite4/feature-vector/2',
-    input_image_shape=[300, 300],
-    name='efficientnet_lite4')
-
 
 # TODO: Document the exposed models.
 @enum.unique
 class SupportedModels(enum.Enum):
   """Image classifier model supported by model maker."""
   MOBILENET_V2 = mobilenet_v2_spec
-  RESNET_50 = resnet_50_spec
   EFFICIENTNET_LITE0 = efficientnet_lite0_spec
   EFFICIENTNET_LITE1 = efficientnet_lite1_spec
-  EFFICIENTNET_LITE2 = efficientnet_lite2_spec
-  EFFICIENTNET_LITE3 = efficientnet_lite3_spec
-  EFFICIENTNET_LITE4 = efficientnet_lite4_spec
 
   @classmethod
   def get(cls, spec: 'SupportedModels') -> 'ModelSpec':