From 2f547eda497d04bc044df31376d860f1557561aa Mon Sep 17 00:00:00 2001
From: Nour shoaib <82571628+nourshoaib@users.noreply.github.com>
Date: Mon, 25 Dec 2023 13:51:57 +0200
Subject: [PATCH 1/2] Add files via upload

---
 visualization/visualize.py | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 visualization/visualize.py

diff --git a/visualization/visualize.py b/visualization/visualize.py
new file mode 100644
index 0000000..e69de29

From 5f0179de535a5f59f0c1d3755bc7e775a810ea31 Mon Sep 17 00:00:00 2001
From: Nour shoaib <82571628+nourshoaib@users.noreply.github.com>
Date: Tue, 26 Dec 2023 08:23:22 +0200
Subject: [PATCH 2/2] Update visualize.py

---
 visualization/visualize.py | 54 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 54 insertions(+)

diff --git a/visualization/visualize.py b/visualization/visualize.py
index e69de29..3df1c68 100644
--- a/visualization/visualize.py
+++ b/visualization/visualize.py
@@ -0,0 +1,54 @@
+class Visualization():
+    def mask2rgb(mask,max_value=1.0):
+        shape = mask.shape
+        if len(shape) == 2:
+            mask = mask[:,:,np.newaxis]
+        h,w,c = mask.shape
+        if c == 3:
+            return mask
+        if c == 4:
+            return mask[:,:,:3]
+    
+        if c > 4:
+            raise ValueError
+    
+        padded = np.zeros((h,w,3),dtype=mask.dtype)
+        padded[:,:,:c] = mask
+        padded = (padded * max_value).astype(np.uint8)
+    
+        return padded
+
+
+    def make_rgb_mask(mask,color=(255,0,0)):
+        h,w = mask.shape[:2]
+        rgb = np.zeros((h,w,3),dtype=np.uint8)
+        rgb[mask == 1.0,:] = color
+        return rgb
+
+    def overlay_rgb_mask(img,mask,sel,alpha):
+
+        sel = sel == 1.0
+        img[sel,:] = img[sel,:] * (1.0 - alpha) + mask[sel,:] * alpha
+        return img
+
+    def overlay_instances_mask(img,instances,cmap,alpha=0.9):
+        h,w = img.shape[:2]
+        overlay = np.zeros((h,w,3),dtype=np.float32)
+
+        _max = instances.max()
+        _cmax = cmap.shape[0]
+    
+
+        if _max == 0:
+            return img
+        elif _max > _cmax:
+            indexes = [(i % _cmax) for i in range(_max)]    
+        else:
+        indexes = random.sample(range(0,_cmax),_max)
+    
+        for i,idx in enumerate(indexes):
+            overlay[instances == i+1,:] = cmap[idx,:]
+    
+        overlay = (overlay * 255.0).astype(np.uint8)
+        viz = overlay_rgb_mask(img,overlay,instances>0,alpha=alpha)
+        return viz