--- a
+++ b/visualizer.py
@@ -0,0 +1,79 @@
+import numpy as np
+import torch
+
+import os
+import io
+import base64
+
+import numpy as np
+import pandas as pd
+import cv2
+import matplotlib.pyplot as plt
+import matplotlib.colors as colors
+
+import time
+from IPython.display import clear_output
+from IPython.display import HTML
+
+
+def show_data_augmentations(img_tensor: torch.Tensor,
+                            mask_tensor: torch.Tensor,
+                            mean: tuple = (0.485, 0.456, 0.406),
+                            std: tuple = (0.229, 0.224, 0.225),
+                            labels: list=["image", "lung", "heart", "trachea"]):
+    
+    img = img_tensor.numpy().transpose(1, 2, 0)
+    img = (img * std + mean).astype("float32")
+    img = np.clip(img, 0, 1)
+    mask = mask_tensor.numpy().transpose(1, 2, 0)
+    data_to_plot = [img, *[mask[:,:, i] for i in range(3)]]
+
+    fig, axes = plt.subplots(nrows=1, ncols=4, figsize=(15, 8))
+    for i, ax in enumerate(axes):
+        ax.imshow(data_to_plot[i])
+        ax.set_title(labels[i])
+
+    plt.show()
+    
+    
+def show_video(video_path: str):
+    """
+    show video in jupyter notebook, agent interaction in environment.
+    Takes - path to video file.
+    Returns - html video player in jupyter notebook.
+    """  
+    video = io.open(video_path, 'r+b').read()
+    encoded = base64.b64encode(video)
+
+    return HTML(data='''<video alt="test" controls>
+    <source src="data:video/mp4;base64,{0}" type="video/mp4" /> </video>'''
+    .format(encoded.decode('ascii')))
+  
+  
+def get_color_info(classes: list = ['lung', 'heart', 'trachea']):
+
+    def get_color(cmap):
+        new_cmap = colors.LinearSegmentedColormap.from_list(
+            (cmap.name, 0.0, 0.0,),
+            cmap(np.linspace(0.0, 0.0, 100))
+            )
+        return new_cmap
+
+    colormaps = [plt.get_cmap(cmap_name) for cmap_name in 
+                ['cool', 'autumn', 'autumn_r']
+                ]
+    arr = np.linspace(0, 50, 100).reshape((10, 10))
+    fig, ax = plt.subplots(1, 3, figsize=(15, 5))
+    for i in range(3):
+        cmap = get_color(colormaps[i])
+        ax[i].axis('off')
+        ax[i].imshow(arr, cmap=cmap)
+        ax[i].set_title(classes[i], fontsize=15)
+
+    fig.suptitle("Color definition", fontsize=20, y=0.99)
+    fig.savefig(f"color_definition.png", bbox_inches='tight', 
+                pad_inches=0.2, dpi=100, format="png")
+    
+    plt.savefig(f"color_definition.svg", bbox_inches='tight',
+                pad_inches=0.2, dpi=100, format="svg")
+    plt.show()