Create app.py

app.py

@@ -0,0 +1,36 @@
+import gradio as gr
+from fastai.vision.all import *
+from os.path import file_exists
+import requests
+
+model_fn = 'quick_224px'
+if not file_exists(model_fn):
+  with requests.get(url, stream=True) as r:
+    r.raise_for_status()
+    with open(model_fn, 'wb') as f:
+      for chunk in r.iter_content(chunk_size=8192):
+        f.write(chunk)
+
+# Load the model
+def open_img(fn:Path): return Image.open(fn).convert('RGB').copy()
+def get_images(path):
+  return get_image_files(path/'train') + get_image_files(path/'test')
+def get_x(item):
+  return np.array(open_img(item).crop((0, 0, 512, 512)))
+def get_y(item):
+  return np.array(open_img(item).crop((512, 0, 1024, 512)))
+sketch_model = load_learner(model_fn)
+
+
+def sketchify(image_path):
+   pred = sketch_model.predict(image_path)
+   np_im = pred[0].permute(1, 2, 0).numpy()
+   return np_im
+    
+    
+
+iface = gr.Interface(fn=sketchify, 
+  inputs=[gr.inputs.Image(shape=(512, 512), type="filepath")], 
+  outputs=[gr.outputs.Image(type="numpy", label="Output Image")]
+)
+iface.launch()