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README.md

@@ -1,12 +1,13 @@
 ---
-title: Is Virtualstaging
-emoji: ⚡
-colorFrom: indigo
-colorTo: blue
+title: Minima
+emoji: 📈
+colorFrom: red
+colorTo: indigo
 sdk: gradio
-sdk_version: 3.34.0
+sdk_version: 2.9.4
 app_file: app.py
 pinned: false
+license: apache-2.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+yep
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference       

app.py

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+import pathlib
+temp = pathlib.PosixPath
+pathlib.PosixPath = pathlib.WindowsPath
+#|export
+#fastai has to be available, i.e. fastai folder
+from fastai.vision.all import *
+import gradio as gr
+import pickle
+
+with open('./model.pkl', 'rb') as f:
+    model = pickle.load(f)
+
+def is_real(x): return x[0].isupper()
+
+#|export
+learn = load_learner('model.pkl')
+
+#|export
+categories =('Virtual Staging','Real')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(im)
+    return dict(zip(categories,map(float,probs)))
+
+#*** We have to cast to float above because KAGGLE does not return number on the answer it returns tensors, and Gradio does not deal with numpy so we have to cast to float
+
+#|export
+#import gradio as gr
+import gradio as gr
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['virtual.jpg','real.jpg','dunno.jpg']
+
+intf = gr.Interface(fn=classify_image,inputs=image,outputs=label,examples=examples)
+intf.launch(inline=False)
+

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6337cb124584166c7d37484f9f6801d1bd1ef8a3961b8f0c42464e7e88c5f7c
+size 46959761