nuevo modelo h5

app.py

@@ -27,23 +27,23 @@ classifier_model.compile(loss=tf.keras.losses.SparseCategoricalCrossentropy(),
                          optimizer='nadam',
                          metrics=['accuracy'])
 
-person_rep = {0: 'DenzelWashington',
- 1: 'Angelina Jolie',
- 2: 'Tom Cruise',
- 3: 'Tom Hanks',
- 4: 'Johnny Depp',
- 5: 'Will Smith',
- 6: 'Scarlett Johansson',
- 7: 'Jennifer Lawrence',
- 8: 'Sandra Bullock',
- 9: 'Megan Fox',
- 10: 'Robert Downey Jr',
- 11: 'Brad Pitt',
- 12: 'Kate Winslet',
- 13: 'Natalie Portman',
- 14: 'Nicole Kidman',
- 15: 'HughJ ackman',
- 16: 'Leonardo DiCaprio'}
+person_rep={0: 'DenzelWashington',
+ 1: 'AngelinaJolie',
+ 2: 'KateWinslet',
+ 3: 'HughJackman',
+ 4: 'ScarlettJohansson',
+ 5: 'JenniferLawrence',
+ 6: 'NicoleKidman',
+ 7: 'SandraBullock',
+ 8: 'LeonardoDiCaprio',
+ 9: 'MeganFox',
+ 10: 'WillSmith',
+ 11: 'TomCruise',
+ 12: 'BradPitt',
+ 13: 'NataliePortman',
+ 14: 'TomHanks',
+ 15: 'JohnnyDepp',
+ 16: 'RobertDowneyJr'}
 
 def predict_image(image_path):
     img = load_img(image_path, target_size=(224, 224))

face_classifier_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:aae463ba877a328fd37eefb67f71d51f68768d0a4a60239f2fb7f310044ac38a
+oid sha256:4fd6ffcd4f98f5074cad8adcaa7e7897885f65ff5f446ab368d834098d3639a1
 size 3219008