added changes to app.py and model.py

app.py

@@ -2,20 +2,20 @@ import gradio as gr
 from PIL import Image
 import cv2
 from ultralytics import YOLO
+import numpy as np
+
 
-# Load model (ensure the path to the weights file is correct)
 model_path = "car_logos.pt"
 detection_model = YOLO(model_path)
 
 def predict_image(pil_image):
     """Process an image and return the annotated image."""
-    # Convert PIL image to NumPy array
+
     frame = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
     
-    # Run YOLO model
+
     results = detection_model.predict(frame, conf=0.5, iou=0.6)
     
-    # Annotate the image
     annotated_frame = results[0].plot()
     
 
@@ -59,7 +59,7 @@ def create_gradio_interface():
             image_button = gr.Button("Process Image")
             image_button.click(fn=predict_image, inputs=image_input, outputs=image_output)
         
-        with gr.Tab("Video Upload"):
+        with gr.Tab("Video Upload for Toyota and Honda logo detection"):
             gr.Markdown("### Upload a Video for Object Detection")
             video_input = gr.Video(label="Input Video")
             video_output = gr.File(label="Annotated Video")

model.py

@@ -14,21 +14,21 @@ settings.update({"wandb": True,
 
 
 model = YOLO("yolov8s.pt")  
-# result = model.train(data="220180T_carlogos-5/data.yaml",
-#                      epochs=30,
-#                      save_period=1,
-#                      batch=50,
-#                      device= "cpu",
-#                      project='Car-Logos',
-#                      plots=True,
-#                      freeze=5,
-#                      lr0= 1e-7,
-#                      optimizer = "Adam" ,
-#                      cls = 0.1,
-#                      )
-
-
-model = YOLO("Car-Logos/train17/weights/best.pt")
+result = model.train(data="220180T_carlogos-5/data.yaml",
+                     epochs=30,
+                     save_period=1,
+                     batch=50,
+                     device= "cpu",
+                     project='Car-Logos',
+                     plots=True,
+                     freeze=5,
+                     lr0= 1e-7,
+                     optimizer = "Adam" ,
+                     cls = 0.1,
+                     )
+
+
+model = YOLO("car_logos.pt")
 validation_results = model.val(data="220180T_carlogos.v5i.yolov8-obb/data.yaml", device="cpu")
 
 model.save("car_logos.pt")

requirements.txt

@@ -1,2 +1,4 @@
 ultralytics
 huggingface_hub
+wandb
+roboflow