final commit

.gitignore

@@ -160,4 +160,7 @@ cython_debug/
 #.idea/
 
 # static
-artifacts/
+artifacts/
+
+# Pytest stuff
+*.xml

app.py

@@ -92,7 +92,10 @@ def display_intro(self) -> None:
         """)
 
     def run(self) -> None:
-        """Run the app"""
+        """
+        Run the app
+        
+        """
 
         self.load_model()
         self.display_intro()

main.py

@@ -44,4 +44,3 @@ def execute_pipeline_stage(stage_name: str, pipeline_obj: object) -> None:
     STAGE_NAME = "MODEL EVALUATION"
     obj = EvaluationPipeline()
     execute_pipeline_stage(STAGE_NAME, obj)
-

research/01_data_ingestion.ipynb

@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -107,21 +107,39 @@
     "        self.config = read_yaml(config_filepath)\n",
     "        self.params = read_yaml(params_filepath)\n",
     "\n",
-    "        create_directories([self.config.artifacts_root])\n",
+    "        # create_directories([self.config.artifacts_root])\n",
     "    \n",
-    "    def get_data_ingestion_config(self) -> DataIngestionConfig:\n",
-    "        config = self.config.data_ingestion\n",
+    "    # def get_data_ingestion_config(self) -> DataIngestionConfig:\n",
+    "    #     config = self.config.data_ingestion\n",
     "\n",
-    "        create_directories([config.root_dir])\n",
+    "    #     create_directories([config.root_dir])\n",
     "\n",
-    "        data_ingestion_config = DataIngestionConfig(\n",
-    "            root_dir=config.root_dir,\n",
-    "            source_URL=config.source_URL,\n",
-    "            local_data_file=config.local_data_file,\n",
-    "            unzip_dir=config.unzip_dir\n",
-    "        )\n",
+    "    #     data_ingestion_config = DataIngestionConfig(\n",
+    "    #         root_dir=config.root_dir,\n",
+    "    #         source_URL=config.source_URL,\n",
+    "    #         local_data_file=config.local_data_file,\n",
+    "    #         unzip_dir=config.unzip_dir\n",
+    "    #     )\n",
     "\n",
-    "        return data_ingestion_config"
+    "    #     return data_ingestion_config"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2024-05-28 13:04:49,790: INFO: common:33: yaml file: config/config.yaml loaded successfully]\n",
+      "[2024-05-28 13:04:49,799: INFO: common:33: yaml file: params.yaml loaded successfully]\n"
+     ]
+    }
+   ],
+   "source": [
+    "config = ConfigurationManager()"
    ]
   },
   {

src/potholeClassifier/components/data_ingestion.py

@@ -13,7 +13,7 @@ def __init__(self, config: DataIngestionConfig) -> None:
         Args:
             config (DataIngestionConfig): Configuration object for data ingestion.
 
-        Returns: 
+        Returns:
             None
         """
         self.config = config

src/potholeClassifier/components/model_evaluation.py

@@ -23,8 +23,8 @@ def __init__(self, config: EvaluationConfig) -> None:
 
         Args:
             config (EvaluationConfig): Configuration object containing evaluation parameters.
-            
-        Returns: 
+
+        Returns:
             None
         """
         self.config = config
@@ -39,7 +39,7 @@ def _validation_generator(self) -> None:
         Args:
             None
 
-        Returns: 
+        Returns:
             None
         """
         datagenerator_kwargs = dict(
@@ -52,8 +52,7 @@ def _validation_generator(self) -> None:
         )
 
         validation_datagenerator = tf.keras.preprocessing.image.ImageDataGenerator(
-            **datagenerator_kwargs
-        )
+            **datagenerator_kwargs)
 
         self.validation_data = validation_datagenerator.flow_from_directory(
             directory=self.config.training_data,
@@ -75,45 +74,43 @@ def _load_model(path: Path) -> tf.keras.Model:
             tf.keras.Model: Loaded machine learning model.
         """
         return tf.keras.models.load_model(path)
-    
+
     def _save_score(self) -> None:
         """
         Saves the evaluation score to a JSON file.
 
         Args:
             None
 
-        Returns: 
+        Returns:
             None
         """
         scores = {"loss": self.score[0], "accuracy": self.score[1]}
         save_json(path=Path("scores.json"), data=scores)
 
-
     def evaluation(self) -> None:
         """
         Performs evaluation of the loaded model using validation data.
 
         Args:
             None
 
-        Returns: 
+        Returns:
             None
         """
         self.model = self.load_model(self.config.path_of_model)
         self._validation_generator()
         self.score = self.model.evaluate(self.validation_data)
         self._save_score()
 
-
     def log_into_mlflow(self) -> None:
         """
         Logs evaluation metrics and the model into MLflow.
 
         Args:
             None
 
-        Returns: 
+        Returns:
             None
         """
         mlflow.set_registry_uri(self.config.mlflow_uri)

src/potholeClassifier/components/model_training.py

@@ -29,7 +29,7 @@ def __init__(self, config: TrainingConfig) -> None:
         Args:
             config (TrainingConfig): The configuration for training the model.
 
-        Returns: 
+        Returns:
             None
         """
         self.config = config
@@ -43,7 +43,7 @@ def get_base_model(self) -> None:
         Args:
             None
 
-        Returns: 
+        Returns:
             None
         """
         self.model = tf.keras.models.load_model(
@@ -60,7 +60,7 @@ def train_valid_generator(self) -> None:
         Args:
             None
 
-        Returns: 
+        Returns:
             None
         """
 
@@ -109,7 +109,7 @@ def train(self) -> None:
         Args:
             callback_list (list): A list of callbacks to be used during training.
 
-        Returns: 
+        Returns:
             None
         """
         self.steps_per_epoch = self.train_generator.samples // self.train_generator.batch_size

src/potholeClassifier/components/prepare_base_model.py

@@ -20,7 +20,7 @@ def __init__(self, config: PrepareBaseModelConfig) -> None:
         Args:
             config (PrepareBaseModelConfig): The configuration for preparing base models.
 
-        Returns: 
+        Returns:
             None
         """
         self.config = config
@@ -78,8 +78,8 @@ def _save_model(path: Path, model: tf.keras.Model) -> None:
         Args:
             path (Path): The path where the model will be saved.
             model (tf.keras.Model): The model to be saved.
-       
-        Returns: 
+
+        Returns:
             None
         """
         model.save(path)

src/potholeClassifier/utils/common.py

@@ -9,6 +9,8 @@
 from pathlib import Path
 from typing import Any
 import base64
+from io import BytesIO
+from PIL import Image
 
 
 @ensure_annotations