Add inference / prediction file

inference_api.py

@@ -0,0 +1,62 @@
+import requests
+import argparse
+import sys
+import base64
+
+# Default examples
+# api = "http://localhost:8080/2015-03-31/functions/function/invocations"
+# file = "./tests/data/boats.jpg"
+
+
+def arg_parser():
+    """Parse arguments"""
+
+    # Create an ArgumentParser object
+    parser = argparse.ArgumentParser(description='Object detection inference via API call')
+    # Add arguments
+    parser.add_argument('--api', type=str, help='URL to server API (with endpoint)', required=True)
+    parser.add_argument('--file', type=str, help='Path to the input image file', required=True)
+    parser.add_argument('-v', '--verbose', action='store_true', help='Increase output verbosity')
+    return parser
+
+
+def main(args=None):
+    """Main function"""
+
+    args = arg_parser().parse_args(args)
+    # Use the arguments
+    if args.verbose:
+        print(f'Input file: {args.file}')
+
+    # Load image
+    with open(args.file, 'rb') as image_file:
+        image_data = image_file.read()
+
+    # Encode the image data in base64
+    encoded_image = base64.b64encode(image_data).decode('utf-8')
+
+    # Prepare the payload
+    payload = {
+        'body': encoded_image
+    }
+
+    # Send request to API
+    # Option 'files': A dictionary of files to send to the specified url
+    # response = requests.post(args.api, files={'image': image_data})
+    # Option 'json': A JSON object to send to the specified url
+    response = requests.post(args.api, json = payload)
+
+    if response.status_code == 200:
+        print('Detection Results:')
+        # Process the response
+        # processed_data = json.loads(response.content)
+        # print('processed_data', processed_data)
+        results = response.json()
+        print("results: ", results)
+    else:
+        print(f"Error: {response.status_code}")
+        print(response.json())
+
+
+if __name__ == "__main__":
+    sys.exit(main(sys.argv[1:]))