merge refactoring

.devcontainer/devcontainer.json

@@ -15,7 +15,7 @@
 	// "forwardPorts": [],
 
 	// Use 'postCreateCommand' to run commands after the container is created.
-	"postCreateCommand": "pip3 install --user -r requirements.txt",
+	"postCreateCommand": "pip3 install --user -r requirements.txt && pip install --upgrade pydantic",
 
 	// Configure tool-specific properties.
 	"customizations": {

app.py

@@ -9,7 +9,7 @@
 import warnings
 import tempfile
 
-from PIL import Image, UnidentifiedImageError
+from PIL import Image
 from datetime import date
 from dotenv import load_dotenv
 from quart import Quart, request, jsonify
@@ -19,6 +19,7 @@
 
 load_dotenv()
 
+from azure.core.exceptions import ResourceNotFoundError, ServiceResponseError
 import model.inference as inference
 from model import request_function
 from datastore import azure_storage_api
@@ -178,7 +179,7 @@ async def before_serving():
             """
         ) #TODO Transform into logging
 
-    except ServerError as e:
+    except (ServerError, inference.ModelAPIErrors) as e:
         print(e)
         raise
 
@@ -207,15 +208,15 @@ async def delete_directory():
                             container_client.delete_blob(blob.name)
                     return jsonify([True]), 200
                 else:
-                    return jsonify(["directory does not exist"]), 400
+                    raise DeleteDirectoryRequestError("directory does not exist")
             else:
-                return jsonify(["failed to mount container"]), 400
+                raise DeleteDirectoryRequestError("failed to mount container")
         else:
-            return jsonify(["missing container or directory name"]), 400
+            raise DeleteDirectoryRequestError("missing container or directory name")
 
-    except DeleteDirectoryRequestError as error:
+    except (KeyError, TypeError, azure_storage_api.MountContainerError, ResourceNotFoundError, DeleteDirectoryRequestError, ServiceResponseError) as error:
         print(error)
-        return jsonify(["DeleteDirectoryRequestError: " + str(error)]), 400
+        return jsonify([f"DeleteDirectoryRequestError: {str(error)}"]), 400
 
 
 @app.post("/dir")
@@ -233,11 +234,11 @@ async def list_directories():
             response = await azure_storage_api.get_directories(container_client)
             return jsonify(response), 200
         else:
-            return jsonify(["Missing container name"]), 400
+            raise ListDirectoriesRequestError("Missing container name")
 
-    except ListDirectoriesRequestError as error:
+    except (KeyError, TypeError, ListDirectoriesRequestError, azure_storage_api.MountContainerError) as error:
         print(error)
-        return jsonify(["ListDirectoriesRequestError: " + str(error)]), 400
+        return jsonify([f"ListDirectoriesRequestError: {str(error)}"]), 400
 
 
 @app.post("/create-dir")
@@ -259,13 +260,13 @@ async def create_directory():
             if response:
                 return jsonify([True]), 200
             else:
-                return jsonify(["directory already exists"]), 400
+                raise CreateDirectoryRequestError("directory already exists")
         else:
-            return jsonify(["missing container or directory name"]), 400
+            raise CreateDirectoryRequestError("missing container or directory name")
 
-    except CreateDirectoryRequestError as error:
+    except (KeyError, TypeError, CreateDirectoryRequestError, azure_storage_api.MountContainerError) as error:
         print(error)
-        return jsonify(["CreateDirectoryRequestError: " + str(error)]), 400
+        return jsonify([f"CreateDirectoryRequestError: {str(error)}"]), 400
 
 
 @app.post("/image-validation")
@@ -318,9 +319,9 @@ async def image_validation():
 
         return jsonify([validator]), 200
 
-    except (UnidentifiedImageError, ImageValidationError) as error:
+    except (KeyError, TypeError, ValueError, ImageValidationError) as error:
         print(error)
-        return jsonify([error.args[0]]), 400
+        return jsonify([f"ImageValidationError: {str(error)}"]), 400
 
 
 @app.post("/inf")
@@ -403,7 +404,7 @@ async def inference_request():
         print(f"Took: {'{:10.4f}'.format(time.perf_counter() - seconds)} seconds") # TODO: Transform into logging
         return jsonify(processed_result_json), 200
 
-    except (KeyError, InferenceRequestError) as error:
+    except (inference.ModelAPIErrors, KeyError, TypeError, ValueError, InferenceRequestError, azure_storage_api.MountContainerError) as error:
         print(error)
         return jsonify(["InferenceRequestError: " + error.args[0]]), 400
 

model/color_palette.py

@@ -2,6 +2,8 @@
 Contains the colors palettes uses to colors the boxes.
 """
 import numpy as np
+from typing import Union
+
 
 # Find color by name or hex code: https://www.color-name.com
 
@@ -74,7 +76,7 @@ def mixing_palettes(dict1: dict, dict2: dict) -> dict:
 
     return {key: dict1[key] + dict2[key] for key in dict1.keys()}
 
-def shades_colors(base_color: str | tuple, num_shades = 5, lighten_factor = 0.15, darken_factor = 0.1) -> tuple:
+def shades_colors(base_color: Union[str, tuple], num_shades = 5, lighten_factor = 0.15, darken_factor = 0.1) -> tuple:
     """
     Generate shades of a color based on the base color.
 

model/inference.py

@@ -10,9 +10,11 @@
 
 import numpy as np
 
-from custom_exceptions import ProcessInferenceResultError
 from model.color_palette import primary_colors, light_colors, mixing_palettes, shades_colors
+from model.model_exceptions import ModelAPIErrors
 
+class ProcessInferenceResultsModelAPIError(ModelAPIErrors) :
+    pass
 
 def generator(list_length):
     for i in range(list_length):
@@ -21,7 +23,7 @@ def generator(list_length):
 
 async def process_inference_results(
         data: dict,
-        imageDims: list[int, int],
+        imageDims: 'list[int, int]',
         area_ratio: float = 0.5,
         color_format: str = "hex"
 ) -> dict:
@@ -138,6 +140,6 @@ async def process_inference_results(
 
         return data
 
-    except (KeyError, TypeError, IndexError) as error:
+    except (KeyError, TypeError, IndexError, ValueError, ZeroDivisionError) as error:
         print(error)
-        raise ProcessInferenceResultError("Error processing inference results") from error
+        raise ProcessInferenceResultsModelAPIError(f"Error while processing inference results :\n {str(error)}") from error

model/model_exceptions.py

@@ -0,0 +1,2 @@
+class ModelAPIErrors(Exception):
+    pass

model/seed_detector.py

@@ -6,11 +6,15 @@
 import io
 import base64
 import json
+from urllib.error import URLError
 
 from PIL import Image
 from collections import namedtuple
-from urllib.request import Request, urlopen, HTTPError
-from custom_exceptions import ProcessInferenceResultError
+from urllib.request import Request, urlopen
+from model.model_exceptions import ModelAPIErrors
+
+class SeedDetectorModelAPIError(ModelAPIErrors) :
+    pass
 
 def process_image_slicing(image_bytes: bytes, result_json: dict) -> list:
     """
@@ -69,7 +73,7 @@ async def request_inference_from_seed_detector(model: namedtuple, previous_resul
         dict: A dictionary containing the result JSON and the images generated from the inference.
 
     Raises:
-        InferenceRequestError: If an error occurs while processing the request.
+        ProcessInferenceResultsError: If an error occurs while processing the request.
     """
     try:
 
@@ -99,5 +103,6 @@ async def request_inference_from_seed_detector(model: namedtuple, previous_resul
             "result_json": result_object,
             "images": process_image_slicing(previous_result, result_object)
         }
-    except HTTPError as e:
-        raise ProcessInferenceResultError(f"An error occurred while processing the request:\n {str(e)}") from None
+    except (KeyError, TypeError, IndexError, ValueError, URLError, json.JSONDecodeError)  as error:
+        print(error)
+        raise SeedDetectorModelAPIError(f"Error while processing inference results :\n {str(error)}") from error

model/six_seeds.py

@@ -5,8 +5,12 @@
 
 import json
 from collections import namedtuple
-from urllib.request import Request, urlopen, HTTPError
-from custom_exceptions import ProcessInferenceResultError
+from urllib.error import URLError
+from urllib.request import Request, urlopen
+from model.model_exceptions import ModelAPIErrors
+
+class SixSeedModelAPIError(ModelAPIErrors) :
+    pass
 
 async def request_inference_from_nachet_6seeds(model: namedtuple, previous_result: str):
     """
@@ -20,7 +24,7 @@ async def request_inference_from_nachet_6seeds(model: namedtuple, previous_resul
         dict: The result of the inference as a JSON object.
 
     Raises:
-        InferenceRequestError: If an error occurs while processing the request.
+        ProcessInferenceResultsError: If an error occurs while processing the request.
     """
     try:
         headers = {
@@ -47,5 +51,6 @@ async def request_inference_from_nachet_6seeds(model: namedtuple, previous_resul
 
         return result_object
 
-    except HTTPError as e:
-        raise ProcessInferenceResultError(f"An error occurred while processing the request:\n {str(e)}") from None
+    except (KeyError, TypeError, IndexError, URLError, json.JSONDecodeError)  as error:
+        print(error)
+        raise SixSeedModelAPIError(f"Error while processing inference results :\n {str(error)}") from error

model/swin.py

@@ -6,9 +6,12 @@
 import json
 
 from collections import namedtuple
-from urllib.request import Request, urlopen, HTTPError
-from custom_exceptions import ProcessInferenceResultError
+from urllib.error import URLError
+from urllib.request import Request, urlopen
+from model.model_exceptions import ModelAPIErrors
 
+class SwinModelAPIError(ModelAPIErrors) :
+    pass
 
 def process_swin_result(img_box:dict, results: dict) -> list:
     """
@@ -27,7 +30,7 @@ def process_swin_result(img_box:dict, results: dict) -> list:
     return img_box
 
 
-async def request_inference_from_swin(model: namedtuple, previous_result: list[bytes]):
+async def request_inference_from_swin(model: namedtuple, previous_result: 'list[bytes]'):
     """
     Perform inference using the SWIN model on a list of images.
 
@@ -39,7 +42,7 @@ async def request_inference_from_swin(model: namedtuple, previous_result: list[b
         The result of the inference.
 
     Raises:
-        InferenceRequestError: If an error occurs while processing the request.
+        ProcessInferenceResultsError: If an error occurs while processing the request.
     """
     try:
         results = []
@@ -58,5 +61,6 @@ async def request_inference_from_swin(model: namedtuple, previous_result: list[b
         print(json.dumps(results, indent=4)) #TODO Transform into logging
 
         return process_swin_result(previous_result.get("result_json"), results)
-    except HTTPError as e:
-       raise ProcessInferenceResultError(f"An error occurred while processing the request:\n {str(e)}") from None
+    except (TypeError, IndexError, AttributeError, URLError, json.JSONDecodeError)  as error:
+        print(error)
+        raise SwinModelAPIError(f"An error occurred while processing the request:\n {str(error)}") from error

model/test.py

@@ -7,8 +7,10 @@
     request_inference_from_nachet_six_seed: Requests inference from the Nachet Six Seed model.
 """
 from collections import namedtuple
-from custom_exceptions import ProcessInferenceResultError
+from model.model_exceptions import ModelAPIErrors
 
+class TestModelAPIError(ModelAPIErrors) :
+    pass
 
 async def request_inference_from_test(model: namedtuple, previous_result: str):
     """
@@ -22,7 +24,7 @@ async def request_inference_from_test(model: namedtuple, previous_result: str):
         dict: The result of the inference as a JSON object.
 
     Raises:
-        InferenceRequestError: If an error occurs while processing the request.
+        ProcessInferenceResultsError: If an error occurs while processing the request.
     """
     try:
         if previous_result == '':
@@ -53,4 +55,5 @@ async def request_inference_from_test(model: namedtuple, previous_result: str):
         ]
 
     except ValueError as error:
-        raise ProcessInferenceResultError("An error occurred while processing the request") from error
+        print(error)
+        raise TestModelAPIError(f"An error occurred while processing the requests :\n {str(error)}") from error

renovate.json

@@ -0,0 +1,6 @@
+{
+  "$schema": "https://docs.renovatebot.com/renovate-schema.json",
+  "extends": [
+    "config:recommended"
+  ]
+}

tests/test_image_validation.py

@@ -49,7 +49,7 @@ def test_invalid_header(self):
         data = json.loads(asyncio.run(response.get_data()))
 
         self.assertEqual(response.status_code, 400)
-        self.assertEqual(data[0], 'invalid file header: data:image/')
+        self.assertEqual(data[0], 'ImageValidationError: invalid file header: data:image/')
 
     @patch("magic.Magic.from_buffer")
     def test_invalid_extension(self, mock_magic_from_buffer):
@@ -71,7 +71,7 @@ def test_invalid_extension(self, mock_magic_from_buffer):
         data = json.loads(asyncio.run(response.get_data()))
 
         self.assertEqual(response.status_code, 400)
-        self.assertEqual(data[0], 'invalid file extension: plain')
+        self.assertEqual(data[0], 'ImageValidationError: invalid file extension: plain')
 
     @patch("PIL.Image.open")
     def test_invalid_size(self, mock_open):
@@ -96,7 +96,7 @@ def test_invalid_size(self, mock_open):
         data = json.loads(asyncio.run(response.get_data()))
 
         self.assertEqual(response.status_code, 400)
-        self.assertEqual(data[0], 'invalid file size: 2000x2000')
+        self.assertEqual(data[0], 'ImageValidationError: invalid file size: 2000x2000')
 
     @patch("PIL.Image.open")
     def test_resizable_error(self, mock_open):
@@ -122,7 +122,7 @@ def test_resizable_error(self, mock_open):
         data = json.loads(asyncio.run(response.get_data()))
 
         self.assertEqual(response.status_code, 400)
-        self.assertEqual(data[0], 'invalid file not resizable')
+        self.assertEqual(data[0], 'ImageValidationError: invalid file not resizable')
 
 if __name__ == '__main__':
     unittest.main()

tests/test_overlapping_in_inference.py

@@ -7,7 +7,7 @@
     light_colors,
     mixing_palettes,
     shades_colors,
-    ProcessInferenceResultError
+    ProcessInferenceResultsModelAPIError,
 )
 
 class TestInferenceProcessFunction(unittest.TestCase):
@@ -107,7 +107,7 @@ def test_process_inference_error(self):
             "totalBoxes": 2
         }
 
-        with self.assertRaises(ProcessInferenceResultError):
+        with self.assertRaises(ProcessInferenceResultsModelAPIError):
             asyncio.run(
                 process_inference_results(data=[data], imageDims=[100, 100]))
 
@@ -116,14 +116,14 @@ def test_process_inference_error(self):
             "totalBoxes": 2
         }
 
-        with self.assertRaises(ProcessInferenceResultError):
+        with self.assertRaises(ProcessInferenceResultsModelAPIError):
             asyncio.run(process_inference_results(data=[data], imageDims=100))
 
         data ={
             "boxes": None,
             "totalBoxes": 2
         }
 
-        with self.assertRaises(ProcessInferenceResultError):
+        with self.assertRaises(ProcessInferenceResultsModelAPIError):
             asyncio.run(
                 process_inference_results(data=[data], imageDims=[100, 100]))