added application file

Dockerfile

@@ -0,0 +1,13 @@
+FROM python:3.10
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+COPY --chown=user . /app
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

cluster_assignments_100.csv

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kmeans_model_100.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7610431307503a43b8b56476449aa1b7a41196578a80564e7b40420cc7259825
+size 20073241

main.py

@@ -0,0 +1,41 @@
+from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi.responses import JSONResponse
+import shutil
+import os
+from vasrch import search_similar_images
+
+# Initialize the FastAPI app
+app = FastAPI()
+
+# Define paths
+UPLOAD_FOLDER = "uploaded_images"
+MODEL_FILENAME = "kmeans_model_100.pkl"
+CSV_FILE = "cluster_assignments_100.csv"
+
+# Ensure the upload folder exists
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+
+@app.post("/search-by-image")
+async def find_similar_images(file: UploadFile = File(...), top_n: int = 30):
+    try:
+        # Save the uploaded file to the upload folder
+        file_path = os.path.join(UPLOAD_FOLDER, file.filename)
+        with open(file_path, "wb") as buffer:
+            shutil.copyfileobj(file.file, buffer)
+
+        # Call the search_similar_images function
+        similar_images = search_similar_images(file_path, MODEL_FILENAME, CSV_FILE, top_n)
+
+        # Return the similar images in JSON format
+        return JSONResponse(content={"similar_images": similar_images})
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+    finally:
+        # Clean up the uploaded file
+        if os.path.exists(file_path):
+            os.remove(file_path)
+
+# Run the app with uvicorn
+# Command: uvicorn fastapi_image_search:app --reload

requirements.txt

@@ -0,0 +1,4 @@
+vasrch
+fastapi
+uvicorn
+python-multipart