Develop

.github/README.pl.md

@@ -3,6 +3,7 @@
 </div>
 <div id="badges">
     <p align="center">
+        <img alt="Github Created At" src="https://img.shields.io/github/created-at/BKDDFS/PerfectFrameAI">
         <img alt="GitHub Downloads (all assets, all releases)" src="https://img.shields.io/github/downloads/BKDDFS/PerfectFrameAI/total?style=flat&color=blue">
         <img alt="GitHub License" src="https://img.shields.io/github/license/BKDDFS/PerfectFrameAI">
         <img alt="GitHub Release" src="https://img.shields.io/github/v/release/BKDDFS/PerfectFrameAI">
@@ -182,6 +183,24 @@
                     <td>bool</td>
                     <td>False</td>
                 </tr>
+                <tr>
+                    <td>--all_frames</td>
+                    <td></td>
+                    <td>
+                        Do pomijania oceniania klatek.
+                    </td>
+                    <td>bool</td>
+                    <td>False</td>
+                </tr>
+                <tr>
+                    <td>--cpu</td>
+                    <td></td>
+                    <td>
+                        Wyłącza korzystanie z GPU. Musisz tego użyć jeśli nie masz GPU. 
+                    </td>
+                    <td>bool</td>
+                    <td>False</td>
+                </tr>
             </tbody>
         </table>
         <p><strong>Przykład dla Best Frames Extraction:</strong></p> 
@@ -434,11 +453,6 @@
             Testy możesz uruchomić instalując zależności z <code>pyproject.toml</code>
             i wpisując w terminal w lokalizacj projektu - <code>pytest</code>.
         </p>
-        <blockquote>
-            Proszę zwrócić uwagę, że w projekcie są dwa foldery <code>tests/</code>.
-            <code>extractor_service</code> i <code>service_initializer</code> mają testy osobno.
-            W pliku common.py znajdują się pliki wpółdzielone przez testy i potrzebne do ich działania.
-        </blockquote>
         <details id="unit">
             <summary>jednostkowe</summary>
             <p>

.gitignore

@@ -9,7 +9,8 @@ input_directory/*
 output_directory/*
 !input_directory/.gitkeep
 !output_directory/.gitkeep
-test_video.mp4
 nima.h5
-common/test_files/best_frames/*
-common/test_files/top_images/*
+tests/test_files/best_frames/*
+tests/test_files/top_images/*
+!tests/test_files/best_frames/.gitkeep
+!tests/test_files/top_images/.gitkeep

README.md

@@ -3,6 +3,7 @@
 </div>
 <div id="badges">
     <p align="center">
+        <img alt="Github Created At" src="https://img.shields.io/github/created-at/BKDDFS/PerfectFrameAI">
         <img alt="GitHub last commit" src="https://img.shields.io/github/last-commit/BKDDFS/PerfectFrameAI">
         <img alt="GitHub License" src="https://img.shields.io/github/license/BKDDFS/PerfectFrameAI">
         <img alt="GitHub Tag" src="https://img.shields.io/github/v/tag/BKDDFS/PerfectFrameAI">
@@ -106,17 +107,19 @@
         <h3>System Requirements:</h3>
         <ul>
             <li>Docker</li>
-            <li>Python 3.10 or higher (method 1 only)</li>
-            <li>Nvidia GPU (recommended)</li>
-            <li>10 GB free disk space</li>
-        </ul> 
+            <li>Python 3.7+ (method 1 only)</li>
+            <li>8GB+ RAM</li>
+            <li>10GB+ free disk space</li>
+        </ul>
+        <p>Lowest tested specs - i5-4300U, 8GB RAM (ThinkPad T440) - 4k video, default 100img/batch.</p>
+        <p>Remember you can always decrease images batch size in schemas.py if you out of RAM.</p>
     </blockquote>
     <details>
         <summary>Install Docker:</summary>
         Docker Desktop: <a href="https://www.docker.com/products/docker-desktop/">https://www.docker.com/products/docker-desktop/</a>
     </details>
     <details>
-        <summary>Install Python v3.10+:</summary>
+        <summary>Install Python v3.7+:</summary>
         MS Store: <a href="https://apps.microsoft.com/detail/9ncvdn91xzqp?hl=en-US&gl=US">https://apps.microsoft.com/detail/9ncvdn91xzqp?hl=en-US&gl=US</a><br>
         Python.org: <a href="https://www.python.org/downloads/">https://www.python.org/downloads/</a>
     </details>
@@ -140,9 +143,17 @@
          <blockquote>
             <p>
                 <strong>Hint for Windows users:</strong><br>
-                As a Windows user you can use <code>quick_demo.bat</code> file.
-                It will run <code>best_frames_extractor</code> with the default values. Just double click on it.
-                You can modify default values in config.py to adjust the application to your needs.
+                As a Windows user, you can use:<br>
+                <code>quick_demo_gpu.bat</code> or <code>quick_demo_cpu.bat</code>
+                if you don't have an Nvidia GPU.<br>
+                It will run <code>best_frames_extractor</code> with the default values.
+                Just double-click on it.
+                You can modify the default values in config.py to adjust the application to your needs.<br>
+                <strong>Warning!</strong><br>
+                Please note that when running the .bat file,
+                Windows Defender may flag it as dangerous.
+                This happens because obtaining a code-signing certificate
+                to prevent this warning requires a paid certificate...
             </p>
         </blockquote>
         <p>Run <code>start.py</code> from the terminal.</p>
@@ -191,6 +202,24 @@
                     <td>bool</td>
                     <td>False</td>
                 </tr>
+                <tr>
+                    <td>--all_frames</td>
+                    <td></td>
+                    <td>
+                        For skipping frames evaluation part.
+                    </td>
+                    <td>bool</td>
+                    <td>False</td>
+                </tr>
+                <tr>
+                    <td>--cpu</td>
+                    <td></td>
+                    <td>
+                        Uses only CPU for processing. If you, don't have GPU you must use it.
+                    </td>
+                    <td>bool</td>
+                    <td>False</td>
+                </tr>
             </tbody>
         </table>
         <p><strong>Example (Best Frames Extraction):</strong></p> 
@@ -203,6 +232,7 @@
             <blockquote><p><i>Does not require Python. Run using Docker Compose.</i></p></blockquote>
         </summary>
         <p>Docker Compose Docs: <a href="https://docs.docker.com/compose/">https://docs.docker.com/compose/</a></p>
+        <p>Remember to delete GPU part in docker-compose.yaml if you don't have GPU!</p>
         <ol>
             <li>Run the service: <br><code>docker-compose up --build -d</code></li>
             <li>Send a request to the chosen endpoint.
@@ -415,11 +445,6 @@
             You can run the tests by installing the dependencies from <code>pyproject.toml</code>
             and typing in the terminal in the project location - <code>pytest</code>.
         </p>
-        <blockquote>
-            Please note that there are two <code>tests/</code> folders in the project.
-            <code>extractor_service</code> and <code>service_initializer</code> have separate tests.
-            The common.py file contains shared files for the tests and necessary for their operation.
-        </blockquote>
         <details id="unit">
             <summary>unit</summary>
             <p>

docker-compose.yaml

@@ -6,8 +6,8 @@ services:
     ports:
       - "8100:8100"
     volumes:
-      - "B:/frames_evaluators/input_directory:/app/input_directory"
-      - "B:/frames_evaluators/output_directory:/app/output_directory"
+      - "./input_directory:/app/input_directory"
+      - "./output_directory:/app/output_directory"
     environment:
       - NVIDIA_VISIBLE_DEVICES=all
       - NVIDIA_DRIVER_CAPABILITIES=compute,video,utility

extractor_service/Dockerfile

@@ -29,6 +29,7 @@ RUN pip install --no-cache-dir -r requirements.txt
 ENV NVIDIA_VISIBLE_DEVICES all
 ENV NVIDIA_DRIVER_CAPABILITIES compute,video,utility
 ENV TF_CPP_MIN_LOG_LEVEL 3
+ENV DOCKER_ENV=1
 
 COPY . .
 

extractor_service/app/dependencies.py

@@ -0,0 +1,95 @@
+"""
+This module provides dependency management for extractors using FastAPI's dependency injection.
+LICENSE
+=======
+Copyright (C) 2024  Bartłomiej Flis
+
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with this program.  If not, see <https://www.gnu.org/licenses/>.
+"""
+from dataclasses import dataclass
+from typing import Type
+
+from fastapi import Depends
+
+from .image_evaluators import InceptionResNetNIMA
+from .image_processors import OpenCVImage
+from .video_processors import OpenCVVideo
+
+
+@dataclass
+class ExtractorDependencies:
+    """
+    Data class to hold dependencies for the extractor.
+
+    Attributes:
+        image_processor (Type[OpenCVImage]): Processor for image processing.
+        video_processor (Type[OpenCVVideo]): Processor for video processing.
+        evaluator (Type[InceptionResNetNIMA]): Evaluator for image quality.
+    """
+    image_processor: Type[OpenCVImage]
+    video_processor: Type[OpenCVVideo]
+    evaluator: Type[InceptionResNetNIMA]
+
+
+def get_image_processor() -> Type[OpenCVImage]:
+    """
+    Provides the image processor dependency.
+
+    Returns:
+        Type[OpenCVImage]: The image processor class.
+    """
+    return OpenCVImage
+
+
+def get_video_processor() -> Type[OpenCVVideo]:
+    """
+    Provides the video processor dependency.
+
+    Returns:
+        Type[OpenCVVideo]: The video processor class.
+    """
+    return OpenCVVideo
+
+
+def get_evaluator() -> Type[InceptionResNetNIMA]:
+    """
+    Provides the image evaluator dependency.
+
+    Returns:
+        Type[InceptionResNetNIMA]: The image evaluator class.
+    """
+    return InceptionResNetNIMA
+
+
+def get_extractor_dependencies(
+        image_processor=Depends(get_image_processor),
+        video_processor=Depends(get_video_processor),
+        evaluator=Depends(get_evaluator)
+) -> ExtractorDependencies:
+    """
+    Provides the dependencies required for the extractor.
+
+    Args:
+        image_processor (Type[OpenCVImage], optional): Dependency injection for image processor.
+        video_processor (Type[OpenCVVideo], optional): Dependency injection for video processor.
+        evaluator (Type[InceptionResNetNIMA], optional): Dependency injection for image evaluator.
+
+    Returns:
+        ExtractorDependencies: All necessary dependencies for the extractor.
+    """
+    return ExtractorDependencies(
+        image_processor=image_processor,
+        video_processor=video_processor,
+        evaluator=evaluator
+    )

extractor_service/app/extractor_manager.py

@@ -19,10 +19,10 @@
 along with this program.  If not, see <https://www.gnu.org/licenses/>.
 """
 import logging
-from typing import Type
 
 from fastapi import HTTPException, BackgroundTasks
 
+from .dependencies import ExtractorDependencies
 from .extractors import Extractor, ExtractorFactory
 from .schemas import ExtractorConfig
 
@@ -35,7 +35,6 @@ class ExtractorManager:
     maintaining system stability.
     """
     _active_extractor = None
-    _config = None
 
     @classmethod
     def get_active_extractor(cls) -> str:
@@ -48,30 +47,28 @@ def get_active_extractor(cls) -> str:
         return cls._active_extractor
 
     @classmethod
-    def start_extractor(cls, background_tasks: BackgroundTasks, config: ExtractorConfig,
-                        extractor_name: str) -> str:
+    def start_extractor(cls, extractor_name: str, background_tasks: BackgroundTasks,
+                        config: ExtractorConfig, dependencies: ExtractorDependencies) -> str:
         """
         Initializes the extractor class and runs the extraction process in the background.
 
         Args:
-            config (ExtractorConfig): A Pydantic model with configuration
-            parameters for the extractor.
-            background_tasks: A FastAPI tool for running tasks in background,
-                which allows non-blocking operation of long-running tasks.
             extractor_name (str): The name of the extractor that will be used.
+            background_tasks (BackgroundTasks): A FastAPI tool for running tasks in background.
+            config (ExtractorConfig): A Pydantic model with extractor configuration.
+            dependencies(ExtractorDependencies): Dependencies that will be used in extractor.
 
         Returns:
             str: Endpoint feedback message with started extractor name.
         """
-        cls._config = config
         cls._check_is_already_extracting()
-        extractor_class = ExtractorFactory.create_extractor(extractor_name)
-        background_tasks.add_task(cls.__run_extractor, extractor_class, extractor_name)
+        extractor = ExtractorFactory.create_extractor(extractor_name, config, dependencies)
+        background_tasks.add_task(cls.__run_extractor, extractor, extractor_name)
         message = f"'{extractor_name}' started."
         return message
 
     @classmethod
-    def __run_extractor(cls, extractor: Type[Extractor], extractor_name: str) -> None:
+    def __run_extractor(cls, extractor: Extractor, extractor_name: str) -> None:
         """
         Run extraction process and clean after it's done.
 
@@ -81,10 +78,9 @@ def __run_extractor(cls, extractor: Type[Extractor], extractor_name: str) -> Non
         """
         try:
             cls._active_extractor = extractor_name
-            extractor(cls._config).process()
+            extractor.process()
         finally:
             cls._active_extractor = None
-            cls._config = None
 
     @classmethod
     def _check_is_already_extracting(cls) -> None: