remove layer support (#692)

.github/workflows/ci.yml

@@ -88,10 +88,6 @@ jobs:
         run: >
           pip install transformers==4.22.1
 
-      - name: Install Layer (0.10.*)
-        run: >
-          pip install -U "layer>=0.10.0,<0.11.0"
-
       - name: Install pycocotools(2.0.5)
         run: >
           pip install pycocotools==2.0.5

.github/workflows/ci_torch1.10.yml

@@ -95,12 +95,6 @@ jobs:
         run: >
           pip install transformers==4.21.2
 
-      - name: Install Layer (0.10.*)
-        if: >
-          matrix.python-version != '3.6'
-        run: >
-          pip install -U "layer>=0.10.0,<0.11.0"
-
       - name: Install pycocotools(2.0.5)
         run: >
           pip install pycocotools==2.0.5

.github/workflows/package_testing.yml

@@ -81,12 +81,6 @@ jobs:
         run: >
           pip install transformers==4.22.1
 
-      - name: Install Layer (0.10.*)
-        if: >
-          matrix.python-version != '3.6'
-        run: >
-          pip install -U "layer>=0.10.0,<0.11.0"
-
       - name: Install pycocotools(2.0.5)
         run: >
           pip install pycocotools==2.0.5

docs/cli.md

@@ -148,7 +148,6 @@ Print related package versions in the current env as:
 06/19/2022 21:24:52 - INFO - sahi.utils.import_utils -   detectron2 version 0.6+cpu is available.
 06/19/2022 21:24:52 - INFO - sahi.utils.import_utils -   transformers version 4.20.0 is available.
 06/19/2022 21:24:52 - INFO - sahi.utils.import_utils -   timm version 0.4.12 is available.
-06/19/2022 21:24:52 - INFO - sahi.utils.import_utils -   layer version 0.10.2510447650 is available.
 06/19/2022 21:24:52 - INFO - sahi.utils.import_utils -   fiftyone version 0.14.2 is available.
 06/19/2022 21:24:52 - INFO - sahi.utils.import_utils -   norfair version 1.0.0 is available.
 ```

sahi/auto_model.py

@@ -35,7 +35,7 @@ def from_pretrained(
             model_type: str
                 Name of the detection framework (example: "yolov5", "mmdet", "detectron2")
             model_path: str
-                Path of the Layer model (ex. '/sahi/yolo/models/yolov5')
+                Path of the detection model (ex. 'model.pt')
             config_path: str
                 Path of the config file (ex. 'mmdet/configs/cascade_rcnn_r50_fpn_1x.py')
             device: str
@@ -74,64 +74,3 @@ def from_pretrained(
             image_size=image_size,
             **kwargs,
         )
-
-    @staticmethod
-    def from_layer(
-        model_path: str,
-        no_cache: bool = False,
-        device: Optional[str] = None,
-        mask_threshold: float = 0.5,
-        confidence_threshold: float = 0.3,
-        category_mapping: Optional[Dict] = None,
-        category_remapping: Optional[Dict] = None,
-        image_size: int = None,
-    ):
-        """
-        Loads a DetectionModel from Layer. You can pass additional parameters in the name to retrieve a specific version
-        of the model with format: ``model_path:major_version.minor_version``
-        By default, this function caches models locally when possible.
-        Args:
-            model_path: str
-                Path of the Layer model (ex. '/sahi/yolo/models/yolov5')
-            no_cache: bool
-                If True, force model fetch from the remote location.
-            device: str
-                Device, "cpu" or "cuda:0"
-            mask_threshold: float
-                Value to threshold mask pixels, should be between 0 and 1
-            confidence_threshold: float
-                All predictions with score < confidence_threshold will be discarded
-            category_mapping: dict: str to str
-                Mapping from category id (str) to category name (str) e.g. {"1": "pedestrian"}
-            category_remapping: dict: str to int
-                Remap category ids based on category names, after performing inference e.g. {"car": 3}
-            image_size: int
-                Inference input size.
-        Returns:
-            Returns an instance of a DetectionModel
-        Raises:
-            ImportError: If Layer is not installed in your environment
-            ValueError: If model path does not match expected pattern: organization_name/project_name/models/model_name
-        """
-        check_requirements(["layer"])
-
-        import layer
-
-        layer_model = layer.get_model(name=model_path, no_cache=no_cache).get_train()
-        if layer_model.__class__.__module__ in ["yolov5.models.common", "models.common"]:
-            model_type = "yolov5"
-        else:
-            raise Exception(f"Unsupported model: {type(layer_model)}. Only YOLOv5 models are supported.")
-
-        model_class_name = MODEL_TYPE_TO_MODEL_CLASS_NAME[model_type]
-        DetectionModel = import_model_class(model_class_name)
-
-        return DetectionModel(
-            model=layer_model,
-            device=device,
-            mask_threshold=mask_threshold,
-            confidence_threshold=confidence_threshold,
-            category_mapping=category_mapping,
-            category_remapping=category_remapping,
-            image_size=image_size,
-        )

sahi/utils/import_utils.py

@@ -1,4 +1,3 @@
-import contextlib
 import importlib.util
 import logging
 import os
@@ -48,7 +47,6 @@ def print_enviroment_info():
     _detectron2_available, _detectron2_version = get_package_info("detectron2")
     _transformers_available, _transformers_version = get_package_info("transformers")
     _timm_available, _timm_version = get_package_info("timm")
-    _layer_available, _layer_version = get_package_info("layer")
     _fiftyone_available, _fiftyone_version = get_package_info("fiftyone")
     _norfair_available, _norfair_version = get_package_info("norfair")