Update app.py
Browse files
app.py
CHANGED
@@ -9,14 +9,30 @@ def psnr(y_true, y_pred):
|
|
9 |
from keras.models import load_model
|
10 |
model = load_model("./MyNet.h5", custom_objects={'psnr': psnr, 'val_psnr': psnr})
|
11 |
|
12 |
-
|
13 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
14 |
#image = image.astype('float32')
|
15 |
-
image = image / 255.0
|
16 |
-
decoded_imgs = model.predict(image)
|
17 |
|
18 |
#decoded_imgs.reshape(256,256,3)
|
19 |
#prediction=model.predict(img_4d)[0]
|
20 |
|
21 |
|
22 |
-
gr.Interface(inputs=image, outputs=decoded_imgs,interpretation='default').launch(debug='True')
|
|
|
9 |
from keras.models import load_model
|
10 |
model = load_model("./MyNet.h5", custom_objects={'psnr': psnr, 'val_psnr': psnr})
|
11 |
|
12 |
+
# γ©γγγγι’ζ°
|
13 |
+
def sepia(input_img):
|
14 |
+
sepia_img = np.asarray(sepia_img)
|
15 |
+
#image = image.astype('float32')
|
16 |
+
sepia_img = sepia_img / 255.0
|
17 |
+
sepia_img = model.predict(sepia_img)
|
18 |
+
return sepia_img
|
19 |
+
|
20 |
+
# γ·γ³γγ«γͺUIγδ½ζ
|
21 |
+
demo = gr.Interface(
|
22 |
+
fn=sepia,
|
23 |
+
inputs=gr.Image(shape=(256, 256)),
|
24 |
+
outputs="image"
|
25 |
+
)
|
26 |
+
|
27 |
+
|
28 |
+
#image = gr.inputs.Image(shape=(256,256))
|
29 |
+
#image = np.asarray(image)
|
30 |
#image = image.astype('float32')
|
31 |
+
#image = image / 255.0
|
32 |
+
#decoded_imgs = model.predict(image)
|
33 |
|
34 |
#decoded_imgs.reshape(256,256,3)
|
35 |
#prediction=model.predict(img_4d)[0]
|
36 |
|
37 |
|
38 |
+
#gr.Interface(inputs=image, outputs=decoded_imgs,interpretation='default').launch(debug='True')
|