abdulrahman2023.py

app.py

@@ -1,21 +1,10 @@
-import gradio as gr
-
-import tensorflow 
-from tensorflow.keras.models import  load_model
-#from livelossplot import PlotLossesKeras
-#from keras.models import load_model
-
-model = load_model('target_xception_model.h5')
-
-class_names={0:'خبيث',1:'حميد'}
-
 def predict_image(img):
     img_4d=img.reshape(-1,299,299,3)
     img_4d=img_4d/255
     prediction=model.predict(img_4d)[0]
     #prediction = [1 if x>0.5 else 0 for x in prediction]
     return {class_names[i]: float(prediction[i]) for i in range(1)}
-    
+    import gradio as gr
 image = gr.inputs.Image(shape=(299,299))
 label = gr.outputs.Label(num_top_classes=1)
 gr.Interface(fn=predict_image, inputs=image,

target_xception_model.h5

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9687877177f9e4692e127e0b366775424c2093da53fcd078eec52601ecb8a008
-size 136052112