diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..28dbf635eed5aec4400f718475a41429ff23e6ae
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,169 @@
+# Models files
+models/
+# Pictures files
+pictures/
+
+.idea/
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
diff --git a/image_processor.py b/image_processor.py
new file mode 100644
index 0000000000000000000000000000000000000000..60843f3bd080c04c5765cf246d42c6085e9e1f3c
--- /dev/null
+++ b/image_processor.py
@@ -0,0 +1,97 @@
+import io
+from typing import Union, Any
+
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
+from ultralytics import YOLO
+
+
+class ImageProcessor:
+    def __init__(self, model: YOLO):
+        self.model = model
+
+    def read_image(self, file):
+        try:
+            if isinstance(file, str):
+                image = Image.open(file)
+            elif hasattr(file, 'file'):
+                image = Image.open(file.file)
+            else:
+                raise ValueError("Unsupported file type")
+
+            if image.mode in ('RGBA', 'L'):
+                image = image.convert('RGB')
+            return image
+        except Exception as e:
+            raise RuntimeError(f"Ошибка при чтении изображения: {e}")
+
+    def process_image(self, image):
+        image_np = np.array(image)
+        results = self.model(image_np)
+        return results
+
+    def draw_detections(self, image, results):
+        draw = ImageDraw.Draw(image)
+        try:
+            font = ImageFont.load_default()
+        except IOError:
+            font = None
+
+        if not font:
+            try:
+                font = ImageFont.truetype("arial.ttf", 15)
+            except IOError:
+                font = ImageFont.load_default()
+
+        boxes = results[0].boxes.xyxy.cpu().numpy()
+        confidences = results[0].boxes.conf.cpu().numpy()
+        classes = results[0].boxes.cls.cpu().numpy()
+        names = results[0].names
+
+        for i, box in enumerate(boxes):
+            x1, y1, x2, y2 = box
+            conf = confidences[i]
+            cls = classes[i]
+            draw.rectangle([x1, y1, x2, y2], outline="red", width=2)
+            label = f"{names[int(cls)]} {conf:.2f}"
+            draw.text((x1, y1), label, fill="red", font=font)
+
+        return image
+
+    def results_to_json(self, results) -> list:
+        boxes = results[0].boxes.xyxy.cpu().numpy()
+        confidences = results[0].boxes.conf.cpu().numpy()
+        classes = results[0].boxes.cls.cpu().numpy()
+        names = results[0].names
+        detections = []
+
+        for i, box in enumerate(boxes):
+            x1, y1, x2, y2 = box
+            conf = confidences[i]
+            cls = classes[i]
+            detection = {
+                "bbox": [int(x1), int(y1), int(x2), int(y2)],
+                "confidence": float(conf),
+                "class": int(cls),
+                "name": names[int(cls)]
+            }
+            detections.append(detection)
+        return detections
+
+    def process(self, file, output_type: str = 'json'):
+        try:
+            image = self.read_image(file)
+            results = self.process_image(image)
+
+            if output_type == 'json':
+                return self.results_to_json(results)
+            elif output_type == 'jpg':
+                image_with_detections = self.draw_detections(image, results)
+                img_byte_arr = io.BytesIO()
+                image_with_detections.save(img_byte_arr, format='JPEG')
+                img_byte_arr.seek(0)
+                return img_byte_arr
+            else:
+                raise ValueError(f"Unsupported output type: {output_type}")
+        except Exception as e:
+            raise RuntimeError(f"Error processing image: {e}")
\ No newline at end of file
diff --git a/test_of_framework.py b/test_of_framework.py
new file mode 100644
index 0000000000000000000000000000000000000000..b5078af79e7e0a033bf8a0da94f11c03bccc126d
--- /dev/null
+++ b/test_of_framework.py
@@ -0,0 +1,27 @@
+import os
+import json
+
+from timacad_framework import TimacadFramework
+
+if __name__ == "__main__":
+    # Определяем директорию
+    base_path = os.path.dirname(os.path.abspath(__file__))
+
+    # Указываем путь к изображениям
+    pic_path = TimacadFramework.get_normalized_path(base_path, "pictures", "2.jpg")
+
+    # Создаем объект TimacadFramework
+    blood_cells_processor = TimacadFramework.create("local", "blood_cells")
+    segmentation_processor = TimacadFramework.create("local", "segmentation_of_fields")
+
+    # Получение json нотации
+    result_json = blood_cells_processor.process(pic_path, output_type='json')
+    # print(result_json)
+
+    with open('output.json', 'w', encoding='utf-8') as f:
+        json.dump(result_json, f, ensure_ascii=False, indent=4)
+
+    # Сохранение аннотированного изображения
+    result_jpg = blood_cells_processor.process(pic_path, output_type='jpg')
+    with open('output.jpg', 'wb') as f:
+        f.write(result_jpg.getbuffer())
\ No newline at end of file
diff --git a/timacad_framework.py b/timacad_framework.py
new file mode 100644
index 0000000000000000000000000000000000000000..c93e14a841d2089949e4c30bbaa769a9b4f647a0
--- /dev/null
+++ b/timacad_framework.py
@@ -0,0 +1,37 @@
+import os
+
+from ultralytics import YOLO
+
+from image_processor import ImageProcessor
+
+
+class TimacadFramework:
+    def __init__(self, model_path: str):
+        try:
+            self.model_path = model_path
+            self.model = YOLO(model_path)
+        except:
+            print('Model not found')
+
+    @classmethod
+    def create(cls, execute: str, model_type: str) -> 'ImageProcessor':
+        if execute != "local":
+            raise ValueError("You can use only local version at this point")
+
+        base_path = os.path.dirname(os.path.abspath(__file__))
+        model_paths = {
+            "blood_cells": cls.get_normalized_path(base_path, "models", "BloodCells.pt"),
+            "segmentation_of_fields": cls.get_normalized_path(base_path, "models", "SegmentationOfFields.pt")
+        }
+
+        if model_type not in model_paths:
+            raise ValueError(f"Unsupported model type: {model_type}")
+
+        builder = cls(model_paths[model_type])
+        return ImageProcessor(builder.model)
+
+    @staticmethod
+    def get_normalized_path(base_path: str, *paths: str) -> str:
+        full_path = os.path.join(base_path, *paths)
+        normalized_path = full_path.replace("\\", "/")
+        return normalized_path
\ No newline at end of file