add sample images and webpage

app.py

@@ -40,6 +40,17 @@ learn = model_type.fastai.learner(dls=[train_dl, valid_dl], model=model, metrics
 
 learn = learn.load('model')
 
+import os
+for root, dirs, files in os.walk(r'sample_images/'):
+    for filename in files:
+        print(filename)
+
+examples = ["sample_images/"+file for file in files] 
+article="<p style='text-align: center'><a href='https://dicksonneoh.com/fridge-detector/' target='_blank'>Blog post</a></p>"
+enable_queue=True
+
+
+
 def show_preds(input_image, display_label, display_bbox, detection_threshold):
 
     if detection_threshold==0: detection_threshold=0.5
@@ -61,7 +72,7 @@ detection_threshold_slider = gr.inputs.Slider(minimum=0, maximum=1, step=0.1, de
 outputs = gr.outputs.Image(type="pil")
 
 # Option 1: Get an image from local drive
-gr_interface = gr.Interface(fn=show_preds, inputs=["image", display_chkbox_label, display_chkbox_box,  detection_threshold_slider], outputs=outputs, title='IceApp - Fridge Object')
+gr_interface = gr.Interface(fn=show_preds, inputs=["image", display_chkbox_label, display_chkbox_box,  detection_threshold_slider], outputs=outputs, title='IceApp - Fridge Object', article=article,examples=examples)
 
 # #  Option 2: Grab an image from a webcam
 # gr_interface = gr.Interface(fn=show_preds, inputs=["webcam", display_chkbox_label, display_chkbox_box,  detection_threshold_slider], outputs=outputs, title='IceApp - COCO', live=False)

requirements.txt

@@ -4,6 +4,5 @@
 
 git+https://github.com/dnth/icevision.git
 icedata
-
 #fastai
 #scikit-image