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Tekken-8-Throw_Detector

Object Detection

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no-supido-de commited on 14 days ago

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@@ -19,4 +19,4 @@ The model underwent 65 training cycles, each consisting of 13 epochs.\
 In each cycle, a batch of 250 randomly selected images from the dataset was used, with at least 40 images depicting throw captures. The batch size was set to 20.\
 The custom top layer added for this task includes a Flatten layer followed by a Dense layer with 128 units and 'relu' activation, a Dropout layer with a rate of 0.4, and a final Dense layer with 1 unit and 'sigmoid' activation to predict throw captures.
-Processing 640x360 image took around 14.5ms on 3060 Ti

 In each cycle, a batch of 250 randomly selected images from the dataset was used, with at least 40 images depicting throw captures. The batch size was set to 20.\
 The custom top layer added for this task includes a Flatten layer followed by a Dense layer with 128 units and 'relu' activation, a Dropout layer with a rate of 0.4, and a final Dense layer with 1 unit and 'sigmoid' activation to predict throw captures.
+Processing 640x360 image took around 14.5ms on 3060 Ti with opened Tekken 8