Update

.gitignore

@@ -105,3 +105,7 @@ ENV/
 .ropeproject
 
 
+*.jpg
+*.txt
+*.png
+Datasets/CUB_200_2011/README

.vscode/settings.json

@@ -1,3 +1,4 @@
 {
-    "python.pythonPath": "D:\\Anaconda\\envs\\ldy\\python.exe"
+    "python.pythonPath": "D:\\Anaconda\\envs\\ldy\\python.exe",
+    "git.ignoreLimitWarning": true
 }

keras_segmentation/data_utils/data_loader.py

@@ -14,8 +14,6 @@
 class_colors = [  ( random.randint(0,255),random.randint(0,255),random.randint(0,255)   ) for _ in range(5000)  ]
 
 
-
-
 def get_pairs_from_paths( images_path , segs_path, recursive = True ):
 	if recursive == True:
 		images = glob.glob( 

run.py

@@ -0,0 +1,22 @@
+import keras_segmentation
+import os
+
+images_path = "./Datasets/CUB_200_2011/images/"
+segs_path = "./Datasets/CUB_200_2011/segmentations/"
+
+model = keras_segmentation.models.unet.vgg_unet(n_classes=51 ,  input_height=416, input_width=608  )
+
+model.train( 
+    train_images =  images_path,
+    train_annotations = segs_path,
+    checkpoints_path = "/tmp/vgg_unet_1" , epochs=5
+)
+
+out = model.predict_segmentation(
+    inp= os.path.join(images_path, "001.Black_footed_Albatross", "Black_footed_Albatross_0001_796111.jpg"),
+    out_fname="/tmp/out.png"
+)
+
+
+import matplotlib.pyplot as plt
+plt.imshow(out)