Upload 3 files

app.py

@@ -0,0 +1,32 @@
+import torch
+import ultralytics
+from ultralytics import YOLO
+import cv2
+import gradio as gr
+
+# ---- FIX for PyTorch 2.6+ ----
+torch.serialization.add_safe_globals([ultralytics.nn.tasks.DetectionModel])
+
+# ---- Load trained YOLO model ----
+model = YOLO("best.pt")  # Make sure 'best.pt' is in the same folder
+
+# ---- Prediction function ----
+def predict(image):
+    # Run inference
+    results = model.predict(source=image, conf=0.25)
+    # Draw boxes on the image
+    result_image = results[0].plot()
+    # Convert BGR → RGB for Gradio
+    return cv2.cvtColor(result_image, cv2.COLOR_BGR2RGB)
+
+# ---- Gradio Interface ----
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="filepath", label="Upload Tea Leaf Image"),
+    outputs=gr.Image(type="numpy", label="Detection Result"),
+    title="Tea Leaf Disease Detection",
+    description="Upload a tea leaf image to detect types of tea leaf diseases using YOLOv8."
+)
+
+if __name__ == "__main__":
+    iface.launch(debug=True)

requirements.txt

@@ -0,0 +1,5 @@
+ultralytics
+opencv-python
+numpy
+gradio
+torch

tea.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b20a9df806ff832661d694de8933bb9eaa1fa121202a3a7e8333a2d0ca8ad4e4
+size 6249123