predict: publish betas

plugins/openvino/package-lock.json

@@ -1,12 +1,12 @@
 {
    "name": "@scrypted/openvino",
-   "version": "0.1.70",
+   "version": "0.1.71",
    "lockfileVersion": 2,
    "requires": true,
    "packages": {
       "": {
          "name": "@scrypted/openvino",
-         "version": "0.1.70",
+         "version": "0.1.71",
          "devDependencies": {
             "@scrypted/sdk": "file:../../sdk"
          }

plugins/openvino/package.json

@@ -42,5 +42,5 @@
    "devDependencies": {
       "@scrypted/sdk": "file:../../sdk"
    },
-   "version": "0.1.70"
+   "version": "0.1.71"
 }

plugins/openvino/src/common/text.py

@@ -46,6 +46,11 @@ async def prepare_text_result(d: ObjectDetectionResult, image: scrypted_sdk.Imag
     image_array = np.array(textImage)
     image_array = image_array.reshape(textImage.height, textImage.width, 1)
     image_tensor = image_array.transpose((2, 0, 1)) / 255
+
+    # test normalize contrast
+    # image_tensor = (image_tensor - np.min(image_tensor)) / (np.max(image_tensor) - np.min(image_tensor))
+
+
     image_tensor = (image_tensor - 0.5) / 0.5
 
     image_tensor = np.expand_dims(image_tensor, axis=0)

plugins/tensorflow-lite/src/predict/recognize.py

@@ -44,8 +44,8 @@ class RecognizeDetection(PredictPlugin):
     def __init__(self, nativeId: str | None = None):
         super().__init__(nativeId=nativeId)
 
-        self.inputheight = 320
-        self.inputwidth = 320
+        self.inputheight = 640
+        self.inputwidth = 640
 
         self.labels = {
             0: "face",
@@ -55,7 +55,7 @@ class RecognizeDetection(PredictPlugin):
         self.loop = asyncio.get_event_loop()
         self.minThreshold = 0.7
 
-        self.detectModel = self.downloadModel("scrypted_yolov9c_flt_320")
+        self.detectModel = self.downloadModel("scrypted_yolov9c_flt")
         self.textModel = self.downloadModel("vgg_english_g2")
         self.faceModel = self.downloadModel("inception_resnet_v1")