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coreml: publish beta

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This commit is contained in:
Koushik Dutta
2026-01-08 08:30:48 -08:00
parent 2cd73b5a6a
commit 70b7b4fa98
3 changed files with 23 additions and 144 deletions
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4
plugins/coreml/package-lock.json generated
View File

@@ -1,12 +1,12 @@
{
"name": "@scrypted/coreml",
"version": "0.1.84",
"version": "0.1.85",
"lockfileVersion": 2,
"requires": true,
"packages": {
"": {
"name": "@scrypted/coreml",
"version": "0.1.84",
"version": "0.1.85",
"devDependencies": {
"@scrypted/sdk": "file:../../sdk"
}

2
plugins/coreml/package.json
View File

@@ -50,5 +50,5 @@
"devDependencies": {
"@scrypted/sdk": "file:../../sdk"
},
"version": "0.1.84"
"version": "0.1.85"
}

161
plugins/coreml/src/coreml/__init__.py
View File

@@ -28,18 +28,11 @@ predictExecutor = concurrent.futures.ThreadPoolExecutor(1, "CoreML-Predict")
availableModels = [
"Default",
"scrypted_yolov10m_320",
"scrypted_yolov10n_320",
"scrypted_yolo_nas_s_320",
"scrypted_yolov9e_320",
"scrypted_yolov9c_320",
"scrypted_yolov9s_320",
"scrypted_yolov9t_320",
"scrypted_yolov6n_320",
"scrypted_yolov6s_320",
"scrypted_yolov8n_320",
"ssdlite_mobilenet_v2",
"yolov4-tiny",
"scrypted_yolov9t_relu_test",
"scrypted_yolov9c_relu_320",
"scrypted_yolov9m_relu_320",
"scrypted_yolov9s_relu_320",
"scrypted_yolov9t_relu_320",
]
@@ -90,52 +83,24 @@ class CoreMLPlugin(
if model != "Default":
self.storage.setItem("model", "Default")
model = "scrypted_yolov9c_relu_320"
self.yolo = "yolo" in model
self.scrypted_yolov10n = "scrypted_yolov10" in model
self.scrypted_yolo_nas = "scrypted_yolo_nas" in model
self.scrypted_yolo = "scrypted_yolo" in model
self.scrypted_model = "scrypted" in model
model_version = "v8"
mlmodel = "model" if self.scrypted_yolo else model
mlmodel = "model"
self.modelName = model
print(f"model: {model}")
if not self.yolo:
# todo convert these to mlpackage
modelFile = self.downloadFile(
f"https://github.com/koush/coreml-models/raw/main/{model}/{mlmodel}.mlmodel",
f"{model}.mlmodel",
files = [
f"{model}/{model}.mlpackage/Data/com.apple.CoreML/weights/weight.bin",
f"{model}/{model}.mlpackage/Data/com.apple.CoreML/{mlmodel}.mlmodel",
f"{model}/{model}.mlpackage/Manifest.json",
]
for f in files:
p = self.downloadFile(
f"https://huggingface.co/scrypted/plugin-models/resolve/main/coreml/{f}",
f"{model_version}/{f}",
)
else:
if self.scrypted_yolo:
files = [
f"{model}/{model}.mlpackage/Data/com.apple.CoreML/weights/weight.bin",
f"{model}/{model}.mlpackage/Data/com.apple.CoreML/{mlmodel}.mlmodel",
f"{model}/{model}.mlpackage/Manifest.json",
]
for f in files:
p = self.downloadFile(
f"https://github.com/koush/coreml-models/raw/main/{f}",
f"{model_version}/{f}",
)
modelFile = os.path.dirname(p)
else:
files = [
f"{model}/{model}.mlpackage/Data/com.apple.CoreML/FeatureDescriptions.json",
f"{model}/{model}.mlpackage/Data/com.apple.CoreML/Metadata.json",
f"{model}/{model}.mlpackage/Data/com.apple.CoreML/weights/weight.bin",
f"{model}/{model}.mlpackage/Data/com.apple.CoreML/{mlmodel}.mlmodel",
f"{model}/{model}.mlpackage/Manifest.json",
]
for f in files:
p = self.downloadFile(
f"https://github.com/koush/coreml-models/raw/main/{f}",
f"{model_version}/{f}",
)
modelFile = os.path.dirname(p)
modelFile = os.path.dirname(p)
self.model = ct.models.MLModel(modelFile)
@@ -248,94 +213,8 @@ class CoreMLPlugin(
return out_dicts
async def detect_once(self, input: Image.Image, settings: Any, src_size, cvss):
objs = []
# run in executor if this is the plugin loop
if self.yolo:
out_dict = await self.queue_batch({self.input_name: input})
if self.scrypted_yolov10n:
results = list(out_dict.values())[0][0]
objs = yolo.parse_yolov10(results)
ret = self.create_detection_result(objs, src_size, cvss)
return ret
if self.scrypted_yolo_nas:
predictions = list(out_dict.values())
objs = yolo.parse_yolo_nas(predictions)
ret = self.create_detection_result(objs, src_size, cvss)
return ret
if self.scrypted_yolo:
results = list(out_dict.values())[0][0]
objs = yolo.parse_yolov9(results)
ret = self.create_detection_result(objs, src_size, cvss)
return ret
out_blob = out_dict["Identity"]
objects = yolo.parse_yolo_region(
out_blob,
(input.width, input.height),
(81, 82, 135, 169, 344, 319),
# (23,27, 37,58, 81,82),
False,
)
for r in objects:
obj = Prediction(
r["classId"],
r["confidence"],
Rectangle(
r["xmin"],
r["ymin"],
r["xmax"],
r["ymax"],
),
)
objs.append(obj)
# what about output[1]?
# 26 26
# objects = yolo.parse_yolo_region(out_blob, (input.width, input.height), (23,27, 37,58, 81,82))
ret = self.create_detection_result(objs, src_size, cvss)
return ret
out_dict = await asyncio.get_event_loop().run_in_executor(
predictExecutor,
lambda: self.model.predict(
{"image": input, "confidenceThreshold": self.minThreshold}
),
)
coordinatesList = out_dict["coordinates"]
for index, confidenceList in enumerate(out_dict["confidence"]):
values = confidenceList
maxConfidenceIndex = max(range(len(values)), key=values.__getitem__)
maxConfidence = confidenceList[maxConfidenceIndex]
if maxConfidence < self.minThreshold:
continue
coordinates = coordinatesList[index]
def torelative(value: float):
return value * self.inputheight
x = torelative(coordinates[0])
y = torelative(coordinates[1])
w = torelative(coordinates[2])
h = torelative(coordinates[3])
w2 = w / 2
h2 = h / 2
l = x - w2
t = y - h2
obj = Prediction(
maxConfidenceIndex, maxConfidence, Rectangle(l, t, l + w, t + h)
)
objs.append(obj)
out_dict = await self.queue_batch({self.input_name: input})
results = list(out_dict.values())[0][0]
objs = yolo.parse_yolov9(results)
ret = self.create_detection_result(objs, src_size, cvss)
return ret