--- a
+++ b/vis/visual.py
@@ -0,0 +1,164 @@
+from enum import IntEnum, unique
+from typing import List
+import cv2
+import numpy as np
+
+
+@unique
+class CocoPart(IntEnum):
+    """Body part locations in the 'coordinates' list."""
+    Nose = 0
+    LEye = 1
+    REye = 2
+    LEar = 3
+    REar = 4
+    LShoulder = 5
+    RShoulder = 6
+    LElbow = 7
+    RElbow = 8
+    LWrist = 9
+    RWrist = 10
+    LHip = 11
+    RHip = 12
+    LKnee = 13
+    RKnee = 14
+    LAnkle = 15
+    RAnkle = 16
+
+
+SKELETON_CONNECTIONS_COCO = [(0, 1, (210, 182, 247)), (0, 2, (127, 127, 127)), (1, 2, (194, 119, 227)),
+                             (1, 3, (199, 199, 199)), (2, 4, (34, 189, 188)), (3, 5, (141, 219, 219)),
+                             (4, 6, (207, 190, 23)), (5, 6, (150, 152, 255)), (5, 7, (189, 103, 148)),
+                             (5, 11, (138, 223, 152)), (6, 8, (213, 176, 197)), (6, 12, (40, 39, 214)),
+                             (7, 9, (75, 86, 140)), (8, 10, (148, 156, 196)), (11, 12, (44, 160, 44)),
+                             (11, 13, (232, 199, 174)), (12, 14,
+                                                         (120, 187, 255)), (13, 15, (180, 119, 31)),
+                             (14, 16, (14, 127, 255))]
+
+
+SKELETON_CONNECTIONS_5P = [('H', 'N', (210, 182, 247)), ('N', 'B', (210, 182, 247)), ('B', 'KL', (210, 182, 247)),
+                           ('B', 'KR', (210, 182, 247)), ('KL', 'KR', (210, 182, 247))]
+
+COLOR_ARRAY = [(210, 182, 247), (127, 127, 127), (194, 119, 227), (199, 199, 199), (34, 189, 188),
+               (141, 219, 219), (207, 190, 23), (150, 152, 255), (189, 103, 148), (138, 223, 152)]
+
+UNMATCHED_COLOR = (180, 119, 31)
+# activity_dict = {
+#     1.0: "Falling forward using hands",
+#     2.0: "Falling forward using knees",
+#     3: "Falling backwards",
+#     4: "Falling sideward",
+#     5: "Falling",
+#     6: "Walking",
+#     7: "Standing",
+#     8: "Sitting",
+#     9: "Picking up an object",
+#     10: "Jumping",
+#     11: "Laying",
+#     12: "False Fall",
+#     20: "None"
+# }
+activity_dict = {
+    1.0: "Falling forward using hands",
+    2.0: "Falling forward using knees",
+    3: "Falling backwards",
+    4: "Falling sideward",
+    5: "FALL",
+    6: "Normal",
+    7: "Normal",
+    8: "Normal",
+    9: "Normal",
+    10: "Normal",
+    11: "Normal",
+    12: "FALL Warning",
+    20: "None"
+}
+
+
+def write_on_image(img: np.ndarray, text: str, color: List) -> np.ndarray:
+    """Write text at the top of the image."""
+    # Add a white border to top of image for writing text
+    img = cv2.copyMakeBorder(src=img,
+                             top=int(0.1 * img.shape[0]),
+                             bottom=0,
+                             left=0,
+                             right=0,
+                             borderType=cv2.BORDER_CONSTANT,
+                             dst=None,
+                             value=[255, 255, 255])
+    for i, line in enumerate(text.split('\n')):
+        y = 30 + i * 30
+        cv2.putText(img=img,
+                    text=line,
+                    org=(0, y),
+                    fontFace=cv2.FONT_HERSHEY_SIMPLEX,
+                    fontScale=0.7,
+                    color=color,
+                    thickness=2)
+
+    return img
+
+
+def visualise(img: np.ndarray, keypoint_sets: List, width: int, height: int, vis_keypoints: bool = False,
+              vis_skeleton: bool = False, CocoPointsOn: bool = False) -> np.ndarray:
+    """Draw keypoints/skeleton on the output video frame."""
+
+    if CocoPointsOn:
+        SKELETON_CONNECTIONS = SKELETON_CONNECTIONS_COCO
+    else:
+        SKELETON_CONNECTIONS = SKELETON_CONNECTIONS_5P
+
+    if vis_keypoints or vis_skeleton:
+        for keypoints in keypoint_sets:
+            if not CocoPointsOn:
+                keypoints = keypoints["keypoints"]
+
+            if vis_skeleton:
+                for p1i, p2i, color in SKELETON_CONNECTIONS:
+                    if keypoints[p1i] is None or keypoints[p2i] is None:
+                        continue
+
+                    p1 = (int(keypoints[p1i][0] * width), int(keypoints[p1i][1] * height))
+                    p2 = (int(keypoints[p2i][0] * width), int(keypoints[p2i][1] * height))
+
+                    if p1 == (0, 0) or p2 == (0, 0):
+                        continue
+
+                    cv2.line(img=img, pt1=p1, pt2=p2, color=color, thickness=3)
+
+    return img
+
+
+def visualise_tracking(img: np.ndarray, keypoint_sets: List, width: int, height: int, num_matched: int, vis_keypoints: bool = False,
+                       vis_skeleton: bool = False, CocoPointsOn: bool = False) -> np.ndarray:
+    """Draw keypoints/skeleton on the output video frame."""
+
+    if CocoPointsOn:
+        SKELETON_CONNECTIONS = SKELETON_CONNECTIONS_COCO
+    else:
+        SKELETON_CONNECTIONS = SKELETON_CONNECTIONS_5P
+
+    if vis_keypoints or vis_skeleton:
+        for i, keypoints in enumerate(keypoint_sets):
+            if keypoints is None:
+                continue
+            if not CocoPointsOn:
+                keypoints = keypoints["keypoints"]
+            if vis_skeleton:
+                for p1i, p2i, color in SKELETON_CONNECTIONS:
+                    if keypoints[p1i] is None or keypoints[p2i] is None:
+                        continue
+
+                    p1 = (int(keypoints[p1i][0] * width), int(keypoints[p1i][1] * height))
+                    p2 = (int(keypoints[p2i][0] * width), int(keypoints[p2i][1] * height))
+
+                    if p1 == (0, 0) or p2 == (0, 0):
+                        continue
+                    if i < num_matched:
+                        color = COLOR_ARRAY[i % 10]
+                    else:
+                        color = UNMATCHED_COLOR
+
+                    cv2.line(img=img, pt1=p1, pt2=p2, color=color, thickness=3)
+
+    return img