coreml: yolov8 default on apple silicon

plugins/coreml/src/coreml/__init__.py

@@ -1,16 +1,20 @@
 from __future__ import annotations
+
+import asyncio
+import concurrent.futures
+import os
+import platform
 import re
-import scrypted_sdk
-from scrypted_sdk import SettingValue, Setting
 from typing import Any, Tuple
-from predict import PredictPlugin, Prediction, Rectangle
+
 import coremltools as ct
-import os
+import numpy as np
+import scrypted_sdk
 from PIL import Image
-import asyncio
-import concurrent.futures
+from scrypted_sdk import Setting, SettingValue
+
 import yolo
-import numpy as np
+from predict import Prediction, PredictPlugin, Rectangle
 
 predictExecutor = concurrent.futures.ThreadPoolExecutor(8, "CoreML-Predict")
 
@@ -33,12 +37,16 @@ def __init__(self, nativeId: str | None = None):
 
         model = self.storage.getItem("model") or "Default"
         if model == "Default":
-            model = "ssdlite_mobilenet_v2"
-        self.yolo = 'yolo' in model
-        self.yolov8 = 'yolov8' in model
+            # model = "ssdlite_mobilenet_v2"
+            if "arm" in platform.processor():
+                model = "yolov8"
+            else:
+                model = "ssdlite_mobilenet_v2"
+        self.yolo = "yolo" in model
+        self.yolov8 = "yolov8" in model
         model_version = "v1"
 
-        print(f'model: {model}')
+        print(f"model: {model}")
 
         if not self.yolo:
             # todo convert these to mlpackage
@@ -52,10 +60,10 @@ def __init__(self, nativeId: str | None = None):
             )
         else:
             if self.yolov8:
-                    modelFile = self.downloadFile(
-                        f"https://github.com/koush/coreml-models/raw/main/{model}/{model}.mlmodel",
-                        f"{model}.mlmodel",
-                    )
+                modelFile = self.downloadFile(
+                    f"https://github.com/koush/coreml-models/raw/main/{model}/{model}.mlmodel",
+                    f"{model}.mlmodel",
+                )
             else:
                 files = [
                     f"{model}/{model}.mlpackage/Data/com.apple.CoreML/FeatureDescriptions.json",
@@ -125,7 +133,7 @@ async def detect_once(self, input: Image.Image, settings: Any, src_size, cvss):
 
         # run in executor if this is the plugin loop
         if self.yolo:
-            input_name = 'image' if self.yolov8 else 'input_1'
+            input_name = "image" if self.yolov8 else "input_1"
             if asyncio.get_event_loop() is self.loop:
                 out_dict = await asyncio.get_event_loop().run_in_executor(
                     predictExecutor, lambda: self.model.predict({input_name: input})
@@ -135,7 +143,7 @@ async def detect_once(self, input: Image.Image, settings: Any, src_size, cvss):
 
             if self.yolov8:
                 out_blob = out_dict["var_914"]
-                var_914 = out_dict['var_914']
+                var_914 = out_dict["var_914"]
                 results = var_914[0]
                 keep = np.argwhere(results[4:] > 0.2)
                 for indices in keep: