diff --git a/utils/flask_rest_api/README.md b/utils/flask_rest_api/README.md
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+## Flask Rest API
+Rest API are commonly used to expose machine learning models to other services. This folder contains an example rest API created using Flask to expose the `yolov5s` model from pytorch hub.
+
+Install Flask in your environment and run:
+
+`$ python3 restapi.py --port 5000`
+
+Then use [curl](https://curl.se/) to perform a request:
+
+`$ curl -X POST -F image=@zidane.jpg 'http://localhost:5000/v1/object-detection/yolov5s'`
+
+The model inference results are returned:
+
+```
+[{'class': 0,
+  'confidence': 0.8197850585,
+  'name': 'person',
+  'xmax': 1159.1403808594,
+  'xmin': 750.912902832,
+  'ymax': 711.2583007812,
+  'ymin': 44.0350036621},
+ {'class': 0,
+  'confidence': 0.5667674541,
+  'name': 'person',
+  'xmax': 1065.5523681641,
+  'xmin': 116.0448303223,
+  'ymax': 713.8904418945,
+  'ymin': 198.4603881836},
+ {'class': 27,
+  'confidence': 0.5661227107,
+  'name': 'tie',
+  'xmax': 516.7975463867,
+  'xmin': 416.6880187988,
+  'ymax': 717.0524902344,
+  'ymin': 429.2020568848}]
+```
+
+An example python script to perform inference using [requests](https://docs.python-requests.org/en/master/) is given in `example_request.py`
diff --git a/utils/flask_rest_api/example_request.py b/utils/flask_rest_api/example_request.py
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+"""Perform test request"""
+import pprint
+import requests
+
+DETECTION_URL = "http://localhost:5000/v1/object-detection/yolov5s"
+TEST_IMAGE = "zidane.jpg"
+
+image_data = open(TEST_IMAGE, "rb").read()
+
+response = requests.post(DETECTION_URL, files={"image": image_data}).json()
+
+pprint.pprint(response)
diff --git a/utils/flask_rest_api/restapi.py b/utils/flask_rest_api/restapi.py
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+++ b/utils/flask_rest_api/restapi.py
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+"""
+Run a rest API exposing the yolov5s object detection model
+"""
+import argparse
+import io
+from PIL import Image
+
+import torch
+from flask import Flask, request
+
+app = Flask(__name__)
+
+DETECTION_URL = "/v1/object-detection/yolov5s"
+
+
+@app.route(DETECTION_URL, methods=["POST"])
+def predict():
+    if not request.method == "POST":
+        return
+
+    if request.files.get("image"):
+        image_file = request.files["image"]
+        image_bytes = image_file.read()
+
+        img = Image.open(io.BytesIO(image_bytes))
+
+        results = model(img, size=640)
+        data = results.pandas().xyxy[0].to_json(orient="records")
+        return data
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Flask api exposing yolov5 model")
+    parser.add_argument("--port", default=5000, type=int, help="port number")
+    args = parser.parse_args()
+
+    model = torch.hub.load(
+        "ultralytics/yolov5", "yolov5s", pretrained=True, force_reload=True
+    ).autoshape()  # force_reload = recache latest code
+    model.eval()
+    app.run(host="0.0.0.0", port=args.port)  # debug=True causes Restarting with stat