detection plugins: remove image splitting logic, let upstream handle …

…that. switch to yolov8_320 as default.

plugins/coreml/package.json

@@ -40,5 +40,5 @@
    "devDependencies": {
       "@scrypted/sdk": "file:../../sdk"
    },
-   "version": "0.1.21"
+   "version": "0.1.23"
 }

plugins/coreml/src/coreml/__init__.py

@@ -37,11 +37,7 @@ def __init__(self, nativeId: str | None = None):
 
         model = self.storage.getItem("model") or "Default"
         if model == "Default":
-            # model = "ssdlite_mobilenet_v2"
-            if "arm" in platform.processor():
-                model = "yolov8n"
-            else:
-                model = "ssdlite_mobilenet_v2"
+            model = "yolov8n_320"
         self.yolo = "yolo" in model
         self.yolov8 = "yolov8" in model
         model_version = "v2"
@@ -111,6 +107,7 @@ async def getSettings(self) -> list[Setting]:
                     "ssdlite_mobilenet_v2",
                     "yolov4-tiny",
                     "yolov8n",
+                    "yolov8n_320",
                 ],
                 "value": model,
             },

plugins/openvino/package.json

@@ -40,5 +40,5 @@
    "devDependencies": {
       "@scrypted/sdk": "file:../../sdk"
    },
-   "version": "0.1.34"
+   "version": "0.1.37"
 }

plugins/openvino/src/ov/__init__.py

@@ -76,20 +76,13 @@ def __init__(self, nativeId: str | None = None):
 
         model = self.storage.getItem('model') or 'Default'
         if model == 'Default':
-            model = 'ssd_mobilenet_v1_coco'
+            model = 'yolov8n_320'
         self.yolo = 'yolo' in model
         self.yolov8 = "yolov8" in model
         self.sigmoid = model == 'yolo-v4-tiny-tf'
 
         print(f'model/mode/precision: {model}/{mode}/{precision}')
 
-        if self.yolov8:
-            self.model_dim = 640
-        elif self.yolo:
-            self.model_dim = 416
-        else:
-            self.model_dim = 300
-
         model_version = 'v4'
         xmlFile = self.downloadFile(f'https://raw.githubusercontent.com/koush/openvino-models/main/{model}/{precision}/{model}.xml', f'{model_version}/{precision}/{model}.xml')
         binFile = self.downloadFile(f'https://raw.githubusercontent.com/koush/openvino-models/main/{model}/{precision}/{model}.bin', f'{model_version}/{precision}/{model}.bin')
@@ -111,6 +104,12 @@ def __init__(self, nativeId: str | None = None):
             self.storage.removeItem('precision')
             self.requestRestart()
 
+        # mobilenet 1,300,300,3
+        # yolov3/4 1,416,416,3
+        # yolov8 1,3,320,320
+        # second dim is always good.
+        self.model_dim = self.compiled_model.inputs[0].shape[2]
+
         labels_contents = open(labelsFile, 'r').read()
         self.labels = parse_label_contents(labels_contents)
 
@@ -132,6 +131,7 @@ async def getSettings(self) -> list[Setting]:
                     'yolo-v3-tiny-tf',
                     'yolo-v4-tiny-tf',
                     'yolov8n',
+                    'yolov8n_320',
                 ],
                 'value': model,
             },
@@ -175,17 +175,19 @@ def get_input_size(self) -> Tuple[int, int]:
     async def detect_once(self, input: Image.Image, settings: Any, src_size, cvss):
         def predict():
             infer_request = self.compiled_model.create_infer_request()
+            # the input_tensor can be created with the shared_memory=True parameter,
+            # but that seems to cause issues on some platforms.
             if self.yolov8:
                 im = np.stack([input])
                 im = im.transpose((0, 3, 1, 2))  # BHWC to BCHW, (n, 3, h, w)
                 im = im.astype(np.float32) / 255.0
                 im = np.ascontiguousarray(im)  # contiguous
-                im = ov.Tensor(array=im, shared_memory=True)
+                im = ov.Tensor(array=im)
                 input_tensor = im
             elif self.yolo:
-                input_tensor = ov.Tensor(array=np.expand_dims(np.array(input), axis=0).astype(np.float32), shared_memory=True)
+                input_tensor = ov.Tensor(array=np.expand_dims(np.array(input), axis=0).astype(np.float32))
             else:
-                input_tensor = ov.Tensor(array=np.expand_dims(np.array(input), axis=0), shared_memory=True)
+                input_tensor = ov.Tensor(array=np.expand_dims(np.array(input), axis=0))
             # Set input tensor for model with one input
             infer_request.set_input_tensor(input_tensor)
             infer_request.start_async()

plugins/openvino/src/yolo/__init__.py

@@ -4,20 +4,29 @@
 
 from predict import Prediction, Rectangle
 
-def parse_yolov8(results, scale = 1):
+defaultThreshold = .2
+
+def parse_yolov8(results, threshold = defaultThreshold, scale = None, confidence_scale  = None):
     objs = []
-    keep = np.argwhere(results[4:] > .2)
+    keep = np.argwhere(results[4:] > threshold)
     for indices in keep:
         class_id = indices[0]
         index = indices[1]
-        confidence = results[class_id + 4, index]
-        x = results[0][index].astype(float) * scale
-        y = results[1][index].astype(float) * scale
-        w = results[2][index].astype(float) * scale
-        h = results[3][index].astype(float) * scale
+        confidence = results[class_id + 4, index].astype(float)
+        x = results[0][index].astype(float)
+        y = results[1][index].astype(float)
+        w = results[2][index].astype(float)
+        h = results[3][index].astype(float)
+        if scale:
+            x = scale(x)
+            y = scale(y)
+            w = scale(w)
+            h = scale(h)
+        if confidence_scale:
+            confidence = confidence_scale(confidence)
         obj = Prediction(
             int(class_id),
-            confidence.astype(float),
+            confidence,
             Rectangle(
                 x - w / 2,
                 y - h / 2,

plugins/tensorflow-lite/.vscode/settings.json

@@ -1,16 +1,16 @@
 
 {
     // docker installation
-    "scrypted.debugHost": "koushik-ubuntu",
-    "scrypted.serverRoot": "/server",
+    // "scrypted.debugHost": "koushik-ubuntu",
+    // "scrypted.serverRoot": "/server",
 
     // pi local installation
     // "scrypted.debugHost": "192.168.2.119",
     // "scrypted.serverRoot": "/home/pi/.scrypted",
 
     // local checkout
-    // "scrypted.debugHost": "127.0.0.1",
-    // "scrypted.serverRoot": "/Users/koush/.scrypted",
+    "scrypted.debugHost": "127.0.0.1",
+    "scrypted.serverRoot": "/Users/koush/.scrypted",
     // "scrypted.debugHost": "koushik-windows",
     // "scrypted.serverRoot": "C:\\Users\\koush\\.scrypted",
 

plugins/tensorflow-lite/package.json

@@ -49,5 +49,5 @@
    "devDependencies": {
       "@scrypted/sdk": "file:../../sdk"
    },
-   "version": "0.1.30"
+   "version": "0.1.38"
 }