Update app.py

app.py

@@ -12,8 +12,8 @@ import io
 from random import choice
 
 
-image_processor_tiny = AutoImageProcessor.from_pretrained("/home/pc-1/Documents/Object detection/weights")
-model_tiny = AutoModelForObjectDetection.from_pretrained("/home/pc-1/Documents/Object detection/weights")
+image_processor_tiny = AutoImageProcessor.from_pretrained("foduucom/object_detection")
+model_tiny = AutoModelForObjectDetection.from_pretrained("foduucom/object_detection")
 
 import gradio as gr
 
@@ -96,7 +96,7 @@ with gr.Blocks(title="YOLOS Object Detection - ClassCat",
     threshold = gr.Slider(0, 1.0, value=0.9, label='threshold')
 
     gr.HTML("""<br/>""")
-    gr.HTML("""<h4 style="color:navy;">4. Then, click "Infer" button to predict object instances. It will take about 10 seconds (yolos-tiny) or 20 seconds (yolos-small).</h4>""")
+    gr.HTML("""<h4 style="color:navy;">4. Then, click "Infer" button to predict object instances.</h4>""")
 
     send_btn = gr.Button("Infer")
     send_btn.click(fn=infer, inputs=[input_image, model, threshold], outputs=[output_image])
@@ -104,7 +104,7 @@ with gr.Blocks(title="YOLOS Object Detection - ClassCat",
     gr.HTML("""<br/>""")
     gr.HTML("""<h4 style="color:navy;">Reference</h4>""")
     gr.HTML("""<ul>""")
-    gr.HTML("""<li><a href="https://huggingface.co/docs/transformers/model_doc/yolos" target="_blank">Hugging Face Transformers - YOLOS</a>""")
+    gr.HTML("""<li><a href="https://huggingface.co/docs/transformers/model_doc/yolos" target="_blank">Hugging Face Transformers - YOLOv8n</a>""")
     gr.HTML("""</ul>""")