Upload app.py

app.py

@@ -12,7 +12,7 @@ configs = [
     },
 ]
 
-config = configs[1]
+config = configs[0]
 
 new_model = tf.keras.models.load_model(config["model"])
 
@@ -20,9 +20,8 @@ def classify_image(inp):
     inp = inp.reshape((-1, config["size"], config["size"], 3))
     prediction = new_model.predict(inp).flatten()
     print(prediction)
-    print(new_model.predict(inp))
     if len(prediction) > 1:
-        probability = 100 * math.exp(prediction[1]) / (math.exp(prediction[0]) + math.exp(prediction[1]))
+        probability = 100 * math.exp(prediction[0]) / (math.exp(prediction[0]) + math.exp(prediction[1]))
     else:
         probability = round(100. / (1 + math.exp(-prediction[0])), 2)
     if probability > 45: