Create app.py

app.py

@@ -0,0 +1,36 @@
+from helper import load_image_from_url, render_results_in_image
+from transformers import pipeline
+
+from transformers.utils import logging
+logging.set_verbosity_error()
+
+from helper import ignore_warnings
+ignore_warnings()
+
+od_pipe = pipeline("object-detection", "facebook/detr-resnet-50")
+
+from PIL import Image
+
+
+
+
+import os
+import gradio as gr
+
+def get_pipeline_prediction(pil_image):
+    
+    pipeline_output = od_pipe(pil_image)
+    processed_image = render_results_in_image(pil_image, pipeline_output)
+    return processed_image
+
+
+demo = gr.Interface(
+  fn=get_pipeline_prediction,
+  inputs=gr.Image(label="Input image", 
+                  type="pil"),
+  outputs=gr.Image(label="Output image with predicted instances",
+                   type="pil")
+)
+
+
+demo.launch(share=True)