Update index.html

index.html

@@ -24,24 +24,28 @@ import gradio as gr
 from transformers_js_py import pipeline
 from filters import convert
 
-# 모델과 tokenizer 파일 경로
-model_path = 'model/'
-tokenizer_path = 'tokenizer.json'
+pipe = await pipeline('object-detection', 'Xenova/detr-resnet-50')
 
-# 모델 및 tokenizer 로드
-pipe = await pipeline('sentiment-analysis', model_path, tokenizer=tokenizer_path)
+async def fn(image):
+	result = await pipe(image)
+	return result
+              
+#demo = gr.Interface.from_pipeline(pipe)
 
-async def predict(text):
-    result = await pipe(text)
-    return result
+async def predict(image):
+  result = await pipe(image)
+  print(result)
+  result = convert(result)
+  print(result) 
+  return image, result
 
 demo = gr.Interface(
-    fn=predict,
-    inputs="text",
-    outputs="text",
-    title="KoELECTRA Sentiment Analysis"
+  fn=predict,
+  inputs=gr.Image(type='pil'),
+  outputs=gr.AnnotatedImage(),
+  title='On-Device Object-Detection with Gradio-Lite & Transformers.js'
 )
-
+         
 demo.launch()
             </gradio-file>
 
@@ -78,4 +82,4 @@ transformers-js-py
             </gradio-requirements>
         </gradio-lite>
     </body>
-</html>
+</html>