Create app.py

app.py

@@ -0,0 +1,30 @@
+import subprocess
+import tempfile
+import time
+from pathlib import Path
+import cv2
+import gradio as gr
+import torch
+from inferer import Inferer
+
+pipeline = Inferer("nateraw/yolov6s", device='cuda')
+print(f"GPU on? {'🟢' if pipeline.device.type != 'cpu' else '🔴'}")
+
+
+def fn_image(image, conf_thres, iou_thres):
+    return pipeline(image, conf_thres, iou_thres)
+
+
+gr.Interface(
+    fn_image,
+    inputs=[
+        gr.Image(source='webcam', streaming=True),
+        gr.Slider(0, 1, value=0.5, label="Confidence Threshold"),
+        gr.Slider(0, 1, value=0.5, label="IOU Threshold"),
+    ],
+    outputs=gr.Image(type="file"),
+    live=True,
+    title="YOLOv8",
+    allow_flagging=False,
+    allow_screenshot=False,
+)