Update app.py

app.py

@@ -5,9 +5,11 @@ import gradio as gr
 import pandas as pd
 from transformers import pipeline
 
+# تحميل النموذج
 model = torch.hub.load('ultralytics/yolov5', 'yolov5s')
 translator = pipeline("translation_en_to_ar", model="Helsinki-NLP/opus-mt-en-ar")
 
+# دالة لاكتشاف الكائنات في الصور
 def detect_and_draw_image(input_image):
     results = model(input_image)
     detections = results.xyxy[0].numpy()
@@ -31,6 +33,7 @@ def detect_and_draw_image(input_image):
 
     return input_image, df
 
+# دالة لاكتشاف الكائنات في الفيديو
 def detect_and_draw_video(video_path):
     cap = cv2.VideoCapture(video_path)
     frames = []
@@ -73,16 +76,19 @@ def detect_and_draw_video(video_path):
 
     return output_path, df
 
+# واجهة صورة
 image_interface = gr.Interface(
     fn=detect_and_draw_image,
     inputs=gr.Image(type="pil", label="Upload Image"),
     outputs=[gr.Image(type="pil"), gr.Dataframe(label="Object Counts")],
     title="Object Detection for Images",
     description="Upload an image to see the objects detected and their counts.",
-        gr.Examples(['assets/MessiVsAlhilal.jpg', 'assets/Manhattan002_0.webp'], inputs=input_image)
-
 )
 
+# إضافة أمثلة للواجهة
+image_interface.examples = ['assets/MessiVsAlhilal.jpg', 'assets/Manhattan002_0.webp']
+
+# واجهة فيديو
 video_interface = gr.Interface(
     fn=detect_and_draw_video,
     inputs=gr.Video(label="Upload Video"),
@@ -91,5 +97,6 @@ video_interface = gr.Interface(
     description="Upload a video to see the objects detected and their counts."
 )
 
+# دمج الواجهات
 app = gr.TabbedInterface([image_interface, video_interface], ["Image Detection", "Video Detection"])
 app.launch(debug=True)