Update yolov5_preview.py

Use 320x320 px input size for new YOLOv5n model to increase fps to 40.

yolov5_preview.py

@@ -7,8 +7,8 @@
 
 This Python script does the following:
 - run a custom YOLOv5 object detection model (.blob format) on-device (Luxonis OAK)
-- use 4K frames downscaled to full FOV LQ frames (e.g. 416x416) as model input
-- show a preview of 4K frames downscaled to full FOV LQ frames (e.g. 416x416) + model output
+- use 4K frames downscaled to full FOV LQ frames (e.g. 320x320) as model input
+- show a preview of 4K frames downscaled to full FOV LQ frames (e.g. 320x320) + model output
 - optional argument:
   "-log" print available Raspberry Pi memory (MB) and RPi CPU utilization (percent) to console
 
@@ -34,8 +34,8 @@
     import psutil
 
 # Set file paths to the detection model and config JSON
-MODEL_PATH = Path("./insect-detect/models/yolov5n_416_openvino_2022.1_5shave.blob")
-CONFIG_PATH = Path("./insect-detect/models/json/yolov5_416.json")
+MODEL_PATH = Path("./insect-detect/models/yolov5n_320_openvino_2022.1_4shave.blob")
+CONFIG_PATH = Path("./insect-detect/models/json/yolov5_320.json")
 
 # Extract detection model metadata from config JSON
 with CONFIG_PATH.open(encoding="utf-8") as f:
@@ -58,10 +58,10 @@
 cam_rgb = pipeline.create(dai.node.ColorCamera)
 #cam_rgb.setImageOrientation(dai.CameraImageOrientation.ROTATE_180_DEG)
 cam_rgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_4_K)
-cam_rgb.setPreviewSize(416, 416) # downscaled LQ frames for model input
+cam_rgb.setPreviewSize(320, 320) # downscaled LQ frames for model input
 cam_rgb.setInterleaved(False)
 cam_rgb.setPreviewKeepAspectRatio(False) # squash full FOV frames to square
-cam_rgb.setFps(30) # frames per second available for focus/exposure/model input
+cam_rgb.setFps(40) # frames per second available for focus/exposure/model input
 
 # Create detection network node and define input + outputs
 nn = pipeline.create(dai.node.YoloDetectionNetwork)