From 75d62a8fe7edb25a724b2b8a1c116dbbc01e0027 Mon Sep 17 00:00:00 2001
From: Tan342 <97234833+Tan342@users.noreply.github.com>
Date: Fri, 19 May 2023 04:08:24 +0700
Subject: [PATCH 1/4] Update model.py

---
 model.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/model.py b/model.py
index 7df5b6889..a852e7914 100644
--- a/model.py
+++ b/model.py
@@ -52,7 +52,7 @@ def unet(pretrained_weights = None,input_size = (256,256,1)):
     conv9 = Conv2D(2, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv9)
     conv10 = Conv2D(1, 1, activation = 'sigmoid')(conv9)
 
-    model = Model(input = inputs, output = conv10)
+    model = Model(inputs, conv10)
 
     model.compile(optimizer = Adam(lr = 1e-4), loss = 'binary_crossentropy', metrics = ['accuracy'])
     

From 20c5aa48762ac73fcee6a5b4c80b61c925470433 Mon Sep 17 00:00:00 2001
From: Tan342 <97234833+Tan342@users.noreply.github.com>
Date: Fri, 19 May 2023 04:16:08 +0700
Subject: [PATCH 2/4] Update main.py

---
 main.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/main.py b/main.py
index f6041b875..e183149f0 100644
--- a/main.py
+++ b/main.py
@@ -18,5 +18,5 @@
 model.fit_generator(myGene,steps_per_epoch=300,epochs=1,callbacks=[model_checkpoint])
 
 testGene = testGenerator("data/membrane/test")
-results = model.predict_generator(testGene,30,verbose=1)
-saveResult("data/membrane/test",results)
\ No newline at end of file
+results = model.predict(testGene,30,verbose=1)
+saveResult("data/membrane/test",results)

From f184784a1fe8a25bd0e8f7884781d97840385cd9 Mon Sep 17 00:00:00 2001
From: Tan342 <97234833+Tan342@users.noreply.github.com>
Date: Fri, 19 May 2023 04:26:04 +0700
Subject: [PATCH 3/4] Update data.py

---
 data.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/data.py b/data.py
index 956497d3f..0d7f1ff01 100644
--- a/data.py
+++ b/data.py
@@ -5,6 +5,7 @@
 import glob
 import skimage.io as io
 import skimage.transform as trans
+from skimage import img_as_uint
 
 Sky = [128,128,128]
 Building = [128,0,0]
@@ -121,4 +122,4 @@ def labelVisualize(num_class,color_dict,img):
 def saveResult(save_path,npyfile,flag_multi_class = False,num_class = 2):
     for i,item in enumerate(npyfile):
         img = labelVisualize(num_class,COLOR_DICT,item) if flag_multi_class else item[:,:,0]
-        io.imsave(os.path.join(save_path,"%d_predict.png"%i),img)
\ No newline at end of file
+        io.imsave(os.path.join(save_path,"%d_predict.png"%i),img_as_uint(img))

From bbfc979ac926c2527bcb705358723363f7fb1e4a Mon Sep 17 00:00:00 2001
From: Tan342 <97234833+Tan342@users.noreply.github.com>
Date: Fri, 19 May 2023 04:44:51 +0700
Subject: [PATCH 4/4] Update main.py

---
 main.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/main.py b/main.py
index e183149f0..4a9c7bf84 100644
--- a/main.py
+++ b/main.py
@@ -15,7 +15,7 @@
 
 model = unet()
 model_checkpoint = ModelCheckpoint('unet_membrane.hdf5', monitor='loss',verbose=1, save_best_only=True)
-model.fit_generator(myGene,steps_per_epoch=300,epochs=1,callbacks=[model_checkpoint])
+model.fit_generator(myGene,steps_per_epoch=300,epochs=10,callbacks=[model_checkpoint])
 
 testGene = testGenerator("data/membrane/test")
 results = model.predict(testGene,30,verbose=1)