diff --git "a/Modules/PoseEstimation/pose_estimation.ipynb" "b/Modules/PoseEstimation/pose_estimation.ipynb"
--- "a/Modules/PoseEstimation/pose_estimation.ipynb"
+++ "b/Modules/PoseEstimation/pose_estimation.ipynb"
@@ -47,25 +47,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
-    "model = YOLO('yolov8n-pose.pt')\n",
+    "import os\n",
+    "import json\n",
     "\n",
-    "def get_keypoints_from_keypoints(video_path, model=YOLO('yolov8n-pose.pt')):\n",
+    "model = YOLO('yolov8n-pose.pt')\n",
     "\n",
+    "def get_keypoints_from_keypoints(video_path):\n",
+    "    save_folder='tmp'\n",
+    "    os.makedirs(save_folder, exist_ok=True)\n",
     "    keypoints = []\n",
     "    results = model(video_path, save=True, show_conf=False, show_boxes=False)\n",
-    "    for frame in results:\n",
-    "        keypoints.append(frame.keypoints.xy)\n",
+    "    for (i, frame) in enumerate(results):\n",
+    "        frame_dict = {}\n",
+    "        frame_dict['frame'] = i\n",
+    "        frame_dict['keypoints'] = frame.keypoints.xy[0].tolist()\n",
+    "        keypoints.append(frame_dict)\n",
     "\n",
-    "    return keypoints"
+    "    file_path = os.path.join(save_folder, 'keypoints.json')\n",
+    "    with open(file_path, 'w') as f:\n",
+    "        json.dump(keypoints, f)\n",
+    "    return file_path"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -83,438 +93,424 @@
       "        boxes = r.boxes  # Boxes object for bbox outputs\n",
       "        masks = r.masks  # Masks object for segment masks outputs\n",
       "        probs = r.probs  # Class probabilities for classification outputs\n",
-      "\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/theorousseaux/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
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-      "video 1/1 (frame 2/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 146.9ms\n",
-      "video 1/1 (frame 3/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 129.1ms\n",
-      "video 1/1 (frame 4/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 124.3ms\n",
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+      "video 1/1 (frame 401/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 154.9ms\n",
+      "video 1/1 (frame 402/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 140.4ms\n",
+      "video 1/1 (frame 403/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 122.5ms\n",
+      "video 1/1 (frame 404/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 174.9ms\n",
+      "video 1/1 (frame 405/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 126.5ms\n",
+      "Speed: 6.9ms preprocess, 168.8ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 576)\n",
+      "Results saved to \u001b[1m/Users/theorousseaux/Documents/Hackathon/FitnessEquation/runs/pose/predict10\u001b[0m\n"
      ]
     }
    ],
    "source": [
-    "keypoints = get_keypoints_from_keypoints(model, '../../data/pose/squat.mp4')"
+    "file_path = get_keypoints_from_keypoints('../../data/pose/squat.mp4')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -540,45 +536,45 @@
     "\n",
     "    return np.degrees(angle)\n",
     "\n",
-    "def compute_left_knee_angle(pose):\n",
+    "def compute_left_knee_angle(keypoints):\n",
     "\n",
     "    \"\"\"\n",
     "    Computes the knee angle.\n",
     "\n",
     "    Args:\n",
-    "        pose (dict): pose dictionary\n",
+    "        keypoints (list): list of keypoints\n",
     "\n",
     "    Returns:\n",
     "        knee_angle (float): knee angle\n",
     "    \"\"\"\n",
     "\n",
-    "    left_hip = pose[0][joints_id_dict['left_hip']]\n",
-    "    left_knee = pose[0][joints_id_dict['left_knee']]\n",
-    "    left_ankle = pose[0][joints_id_dict['left_ankle']]\n",
+    "    left_hip = keypoints[joints_id_dict['left_hip']]\n",
+    "    left_knee = keypoints[joints_id_dict['left_knee']]\n",
+    "    left_ankle = keypoints[joints_id_dict['left_ankle']]\n",
     "\n",
     "    knee_angle = calculate_angle(left_hip, left_knee, left_ankle)\n",
     "\n",
     "    return knee_angle\n",
     "\n",
-    "def compute_right_knee_angle(pose):\n",
-    "\n",
-    "    \"\"\"\n",
-    "    Computes the knee angle.\n",
-    "\n",
-    "    Args:\n",
-    "        pose (dict): pose dictionary\n",
-    "\n",
-    "    Returns:\n",
-    "        knee_angle (float): knee angle\n",
-    "    \"\"\"\n",
-    "\n",
-    "    right_hip = pose[0][joints_id_dict['right_hip']]\n",
-    "    right_knee = pose[0][joints_id_dict['right_knee']]\n",
-    "    right_ankle = pose[0][joints_id_dict['right_ankle']]\n",
-    "\n",
-    "    knee_angle = calculate_angle(right_hip, right_knee, right_ankle)\n",
-    "\n",
-    "    return knee_angle\n",
+    "def compute_right_knee_angle(keypoints):\n",
+    "    \n",
+    "        \"\"\"\n",
+    "        Computes the knee angle.\n",
+    "    \n",
+    "        Args:\n",
+    "            keypoints (list): list of keypoints\n",
+    "    \n",
+    "        Returns:\n",
+    "            knee_angle (float): knee angle\n",
+    "        \"\"\"\n",
+    "    \n",
+    "        right_hip = keypoints[joints_id_dict['right_hip']]\n",
+    "        right_knee = keypoints[joints_id_dict['right_knee']]\n",
+    "        right_ankle = keypoints[joints_id_dict['right_ankle']]\n",
+    "    \n",
+    "        knee_angle = calculate_angle(right_hip, right_knee, right_ankle)\n",
+    "    \n",
+    "        return knee_angle   \n",
     "\n",
     "def moving_average(data, window_size):\n",
     "\n",
@@ -600,6 +596,429 @@
     "    return avg"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       " 161.05424553148129,\n",
+       " 161.95292931754383]"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def compute_right_knee_angle_list(json_path: str):\n",
+    "    keypoints_list = json.load(open(json_path))\n",
+    "    right_knee_angle_list = []\n",
+    "    for keypoints in keypoints_list:\n",
+    "        right_knee_angle = compute_right_knee_angle(keypoints['keypoints'])\n",
+    "        right_knee_angle_list.append(right_knee_angle)\n",
+    "    return moving_average(right_knee_angle_list, 10)\n",
+    "\n",
+    "compute_right_knee_angle_list(file_path)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 6,