Upload 6 files

.gitignore

@@ -0,0 +1,162 @@
+# 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/

Model/yolov8l.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:64c9115303f6a25575f82200d1b22ec409fa6bd7d08d0313884fc20d919478cd
+size 87792836

main.py

@@ -0,0 +1,99 @@
+import io
+import base64
+import numpy as np
+import cv2
+from PIL import Image as PILImage
+from ultralytics import YOLO
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from typing import Optional
+from matplotlib import cm
+
+from fastapi.middleware.cors import CORSMiddleware
+
+app = FastAPI()
+
+# Add CORS middleware to allow requests from anywhere
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Allow all origins
+    allow_credentials=True,
+    allow_methods=["*"],  # Allow all HTTP methods
+    allow_headers=["*"],  # Allow all headers
+)
+
+class ImageRequest(BaseModel):
+    image: str  # Base64-encoded image string
+
+class ObjectDetectionSystem:
+    def __init__(self, model_path='Model/yolov8l.pt'):
+        self.yolo_model = YOLO(model_path)
+        self.color_map = cm.get_cmap("tab20", len(self.yolo_model.names))  # Generate distinct colors
+
+    def detect_objects(self, image_base64: str, confidence_threshold: float = 0.5):
+        try:
+            # Decode Base64 and convert to NumPy array
+            image_data = base64.b64decode(image_base64)
+            pil_image = PILImage.open(io.BytesIO(image_data)).convert("RGB")
+            image_np = np.array(pil_image)
+
+            # Resize image for consistent processing
+            input_size = 640  # Example size for YOLO models
+            height, width, _ = image_np.shape
+            scale = input_size / max(height, width)
+            resized_image = cv2.resize(image_np, (int(width * scale), int(height * scale)))
+
+            # Perform object detection
+            results = self.yolo_model(resized_image)
+
+            # Draw results on image
+            output_image = resized_image.copy()
+            for result in results:
+                boxes = result.boxes
+                for box in boxes:
+                    x1, y1, x2, y2 = box.xyxy[0].cpu().numpy()
+                    x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
+                    confidence = float(box.conf[0])
+                    class_id = int(box.cls[0])
+                    class_name = self.yolo_model.names[class_id]
+
+                    if confidence > confidence_threshold:
+                        # Generate color for this class
+                        color = tuple(int(c * 255) for c in self.color_map(class_id)[:3])
+
+                        # Draw bounding box
+                        cv2.rectangle(output_image, (x1, y1), (x2, y2), color, 2)
+
+                        # Add label with confidence
+                        label = f'{class_name} ({confidence:.2f})'
+                        label_size, baseline = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
+                        label_y = max(y1, label_size[1] + 10)
+                        cv2.rectangle(output_image, (x1, label_y - label_size[1] - 10),
+                                      (x1 + label_size[0], label_y + baseline - 10), color, -1)
+                        cv2.putText(output_image, label, (x1, label_y - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1)
+
+            # Convert back to Base64
+            output_pil = PILImage.fromarray(output_image)
+            buffered = io.BytesIO()
+            output_pil.save(buffered, format="PNG")
+            encoded_image = base64.b64encode(buffered.getvalue()).decode("utf-8")
+            
+            return encoded_image
+
+        except Exception as e:
+            raise HTTPException(status_code=500, detail=str(e))
+
+# Initialize the detector with a more advanced model
+detector = ObjectDetectionSystem('Model/yolov8l.pt')
+
+@app.post("/detect")
+async def detect_objects(request: ImageRequest):
+    try:
+        result_image = detector.detect_objects(request.image)
+        return {"processed_image": result_image}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/")
+async def root():
+    return {"message": "Object Detection API is running"}