random

app.py

@@ -5,15 +5,10 @@ import tensorflow as tf
 import random 
 from tensorflow import keras
 
-from cloudpathlib import CloudPath
-
-cp = CloudPath("s3://soteria-ml-models/")
-cp.download_to("./models")
-
 
 damage_types = np.array(sorted(['disaster happened', 'no disaster happened']))
 disaster_types = np.array(sorted(['volcano', 'flooding', 'earthquake', 'fire', 'wind', 'tsunami']))
-model = keras.models.load_model('./models/disaster-classification')
+# model = keras.models.load_model('./models/disaster-classification')
 
 def damage_classification(img):
     prediction = np.random.rand(1, 2)[0]
@@ -22,8 +17,8 @@ def damage_classification(img):
 def disaster_classification(img):
     image = np.zeros((1, 1024, 1024, 3), dtype=np.uint8)
     image[0] = img
-    prediction = model.predict(image).tolist()[0]
-    # prediction = np.random.rand(1, 6)[0]
+    # prediction = model.predict(image).tolist()[0]
+    prediction = np.random.rand(1, 6)[0]
     return {disaster_types[i]: prediction[i] for i in range(len(disaster_types))}
 
 iface = gr.Interface(