Upload app.py

app.py

@@ -68,17 +68,53 @@ title = "Smartathon Phase2 Demo - Baseer"
 description = "This demo introduces an interactive playground for our trained Detectron2 model."
 article = '<p>Detectron model is available from our repository <a href="https://github.com/asalhi/Smartathon-Baseer">here</a>.</p>'
 
-gr.Interface(
-    inference,
-    [gr.inputs.Textbox(label="Image URL", placeholder=""),
-     gr.inputs.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image"),
-     gr.Slider(minimum=0.0, maximum=1.0, value=0.4, label="Minimum score"),
-    ],
-    gr.outputs.Image(type="pil", label="Output"),
-    #gr.Examples(['./d1.jpeg', './d2.jpeg', './d3.jpeg','./d4.jpeg','./d5.jpeg','./d6.jpeg'], inputs=gr.inputs.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image")),
-    title=title,
-    description=description,
-    article=article,
-    examples=[['./d1.jpeg'], ['./d2.jpeg'], ['./d3.jpeg'],['./d4.jpeg'],['./d5.jpeg'],['./d6.jpeg']],
-    cache_examples=False).launch()
-    #examples=['./d1.jpeg', './d2.jpeg', './d3.jpeg','./d4.jpeg','./d5.jpeg','./d6.jpeg']
+# gr.Interface(
+#     inference,
+#     [gr.inputs.Textbox(label="Image URL", placeholder=""),
+#      gr.inputs.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image"),
+#      gr.Slider(minimum=0.0, maximum=1.0, value=0.4, label="Minimum score"),
+#     ],
+#     gr.outputs.Image(type="pil", label="Output"),
+#     #gr.Examples(['./d1.jpeg', './d2.jpeg', './d3.jpeg','./d4.jpeg','./d5.jpeg','./d6.jpeg'], inputs=gr.inputs.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image")),
+#     title=title,
+#     description=description,
+#     article=article,
+#     #examples=[['./d1.jpeg'], ['./d2.jpeg'], ['./d3.jpeg'],['./d4.jpeg'],['./d5.jpeg'],['./d6.jpeg']],
+#     examples = gr.Examples(['./d1.jpeg', './d2.jpeg', './d3.jpeg','./d4.jpeg','./d5.jpeg','./d6.jpeg'], inputs=gr.inputs.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image")),
+#     cache_examples=False).launch()
+#     #examples=['./d1.jpeg', './d2.jpeg', './d3.jpeg','./d4.jpeg','./d5.jpeg','./d6.jpeg']
+
+
+with gr.Blocks(title=title,
+                    description=description,
+                    article=article
+               ) as demo:
+
+    # gr.HTML("""<div style="font-family:'Times New Roman', 'Serif'; font-size:16pt; font-weight:bold; text-align:center; color:royalblue;">Detectron2 Object Detection</div>""")
+    #
+    # gr.HTML("""<h4 style="color:navy;">1-a. Select an example by clicking a thumbnail below.</h4>""")
+    #
+    # gr.HTML("""<h4 style="color:navy;">1-b. Or upload an image by clicking on the canvas.</h4>""")
+
+    with gr.Row():
+        input_url = gr.Textbox(label="Image URL", placeholder="")
+        input_image = gr.Image(type="filepath", image_mode="RGB", source="upload", optional=False, label="Input Image")
+        output_image = gr.Image(type="pil", label="Output")
+
+    gr.Examples(['./d1.jpeg', './d2.jpeg', './d3.jpeg','./d4.jpeg','./d5.jpeg','./d6.jpeg'], inputs=input_image)
+
+    # gr.HTML("""<br/>""")
+    # gr.HTML("""<h4 style="color:navy;">2. Then, click "Infer" button to predict object instances. It will take about 15-20 seconds (on cpu)</h4>""")
+
+    send_btn = gr.Button("Submit")
+    send_btn.click(fn=infer, inputs=[[input_url],[input_image]], outputs=[output_image])
+
+    # gr.HTML("""<br/>""")
+    # gr.HTML("""<h4 style="color:navy;">Reference</h4>""")
+    # gr.HTML("""<ul>""")
+    # gr.HTML("""<li><a href="https://colab.research.google.com/drive/16jcaJoc6bCFAQ96jDe2HwtXj7BMD_-m5" target="_blank">Detectron2 Tutorial</a>""")
+    # gr.HTML("""</ul>""")
+
+
+#demo.queue()
+demo.launch() # debug=True)