docker 1

Dockerfile

@@ -14,13 +14,13 @@ RUN apt-get update && apt-get install -y \
     libxrender-dev \
     && rm -rf /var/lib/apt/lists/*
 
-# Python environment setup
+# Upgrade pip
 RUN pip install --upgrade pip setuptools wheel
 
-# Install dlib separately to avoid build failure from other packages
+# Install dlib separately to avoid issues
 RUN pip install dlib --use-pep517 --no-build-isolation
 
-# Install all Python dependencies including face_recognition
+# Install Python dependencies
 COPY requirements.txt .
 RUN pip install -r requirements.txt
 
@@ -28,8 +28,5 @@ RUN pip install -r requirements.txt
 COPY app/ /app/
 WORKDIR /app
 
-# Expose FastAPI port
-EXPOSE 7860
-
-# Run the app
-CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]
+# Run the app with uvicorn (no need to expose ports for Hugging Face)
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

app/main.py

@@ -1,4 +1,4 @@
-from fastapi import FastAPI, UploadFile, File, Form, HTTPException, Depends
+from fastapi import FastAPI, UploadFile, File, Form
 import os
 import shutil
 import numpy as np
@@ -6,28 +6,24 @@ import face_recognition
 from PIL import Image, UnidentifiedImageError
 import io
 from typing import List, Dict, Set
-import uvicorn
 
 app = FastAPI()
 
 BASE_DIR = "uploaded_images"
-
-# Ensure base directory exists
 os.makedirs(BASE_DIR, exist_ok=True)
 
-faculty_assignments: Dict[tuple, Set[str]] = {}  # Dictionary to track faculties assigned to folders
+faculty_assignments: Dict[tuple, Set[str]] = {}
 
 def get_org_folder_path(org_name: str, folder_name: str):
     return os.path.join(BASE_DIR, org_name, folder_name)
 
 def load_student_encodings(folder_path: str):
-    """Load student images from a given folder and return encodings."""
     students = {}
     if not os.path.exists(folder_path):
         return {"error": f"Folder '{folder_path}' does not exist"}
 
     for filename in os.listdir(folder_path):
-        if filename.endswith(".jpg") or filename.endswith(".png"):
+        if filename.lower().endswith((".jpg", ".jpeg", ".png")):
             image_path = os.path.join(folder_path, filename)
             image = face_recognition.load_image_file(image_path)
             encoding = face_recognition.face_encodings(image)
@@ -37,7 +33,6 @@ def load_student_encodings(folder_path: str):
     return students
 
 def process_image(image: np.ndarray, students: dict):
-    """Helper function to compare uploaded image with stored student images."""
     group_face_encodings = face_recognition.face_encodings(image)
     if not group_face_encodings:
         return {"error": "No faces detected in the image"}
@@ -53,8 +48,11 @@ def process_image(image: np.ndarray, students: dict):
     return {"missing_students": list(missing_students)}
 
 @app.post("/create_folder/")
-async def create_folder(org_name: str = Form(...), folder_name: str = Form(...), files: List[UploadFile] = File(...)):
-    """Creates a new folder under an organization and stores images."""
+async def create_folder(
+    org_name: str = Form(...),
+    folder_name: str = Form(...),
+    files: List[UploadFile] = File(...)
+):
     org_path = os.path.join(BASE_DIR, org_name)
     folder_path = os.path.join(org_path, folder_name)
     os.makedirs(folder_path, exist_ok=True)
@@ -64,36 +62,37 @@ async def create_folder(org_name: str = Form(...), folder_name: str = Form(...),
         with open(file_path, "wb") as buffer:
             shutil.copyfileobj(file.file, buffer)
 
-    return {"message": f"Folder '{folder_name}' created under organization '{org_name}' with {len(files)} images."}
+    return {
+        "message": f"Folder '{folder_name}' created under organization '{org_name}' with {len(files)} images."
+    }
 
 @app.post("/check_attendance/")
-async def check_attendance(org_name: str = Form(...), folder_name: str = Form(...), faculty_id: str = Form(...), file: UploadFile = File(...)):
-    """Check attendance using an uploaded image, ensuring only assigned faculty can check."""
+async def check_attendance(
+    org_name: str = Form(...),
+    folder_name: str = Form(...),
+    faculty_id: str = Form(...),
+    file: UploadFile = File(...)
+):
     folder_path = get_org_folder_path(org_name, folder_name)
-
-    # Validate faculty access
     folder_key = (org_name, folder_name)
+
     if faculty_id not in faculty_assignments.get(folder_key, set()):
         return {"error": "Unauthorized access. Only assigned faculty members can check attendance."}
 
-    # Load student encodings from the specified folder
     students = load_student_encodings(folder_path)
     if "error" in students:
         return students
 
     try:
-        # Read and process uploaded image
         image_bytes = await file.read()
-        image = Image.open(io.BytesIO(image_bytes))
-        image = image.convert("RGB")
+        image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
         image_array = np.array(image)
-
         return process_image(image_array, students)
-
     except UnidentifiedImageError:
-        return {"error": "Invalid image format. Please upload a valid image file (JPG or PNG)."}
+        return {"error": "Invalid image format. Please upload a valid JPG or PNG image."}
     except Exception as e:
         return {"error": f"Internal server error: {str(e)}"}
 
 if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)