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import io
from fastapi import FastAPI, File, UploadFile
from fastapi.responses import JSONResponse, StreamingResponse
from PIL import Image, UnidentifiedImageError
from routes.segmentation import segment_chess_board
from routes.detection import detect_pieces
from routes.fen_generator import gen_fen
from typing import List, Dict, Any, Union
from pydantic import BaseModel
app = FastAPI()
class DetectionResults(BaseModel):
boxes: list
confidences: list
classes: list
@app.get("/")
async def read_root():
return {
"name": "Narendra",
"age": 20,
"Gender": "Male"
}
@app.post("/getSeg")
async def get_seg(file: UploadFile = File(...)):
print(f'Image received: {file.filename}')
try:
image_content = await file.read()
if not image_content:
return JSONResponse(content={"error": "Empty file uploaded"}, status_code=400)
try:
image = Image.open(io.BytesIO(image_content))
except UnidentifiedImageError:
return JSONResponse(content={"error": "Invalid image format"}, status_code=400)
# If segment_chess_board is async, use `await`, otherwise remove `await`
segmented_image = await segment_chess_board(image)
if isinstance(segmented_image, dict):
return JSONResponse(content=segmented_image, status_code=400)
# Save to in-memory bytes
img_bytes = io.BytesIO()
segmented_image.save(img_bytes, format="PNG")
img_bytes.seek(0)
print("Image successfully processed and returned")
return StreamingResponse(
img_bytes,
media_type="image/png",
headers={"Content-Disposition": "inline; filename=output.png"}
)
except Exception as e:
return JSONResponse(content={"error": str(e)}, status_code=500)
@app.post("/getCoords")
async def get_coords(file: UploadFile = File(...)):
try:
image_content = await file.read()
if not image_content:
print("No image found")
return JSONResponse(content={"error": "Empty file uploaded"}, status_code=400)
try:
image = Image.open(io.BytesIO(image_content))
except UnidentifiedImageError:
return JSONResponse(content={"error": "Invalid image format"}, status_code=400)
detection_results = await detect_pieces(image)
if "error" in detection_results:
return JSONResponse(content=detection_results, status_code=400)
print("Image successfully processed and returned")
return JSONResponse(content={"detections": detection_results}, status_code=200)
except Exception as e:
print(f"Unexpected error: {str(e)}")
return JSONResponse(content={"error": "Unexpected error occurred", "details": str(e)}, status_code=500)
@app.post("/getFen")
async def get_fen(file : UploadFile = File(), perspective : str = "w", next_to_move : str = "w"):
if perspective not in ["w" , "b"]:
return JSONResponse(content={"error" : "Perspective should be w (white) or b (black)"}, status_code=500)
if next_to_move not in ["w" , "b"]:
return JSONResponse(content={"error" : "next to move should be w (white) or b (black)"}, status_code=500)
try:
image_content = await file.read()
if not image_content:
return JSONResponse(content={"error": "Empty file uploaded"}, status_code=400)
try:
image = Image.open(io.BytesIO(image_content))
except UnidentifiedImageError:
return JSONResponse(content={"error": "Invalid image format"}, status_code=400)
segmented_image = await segment_chess_board(image)
if isinstance(segmented_image, dict):
return JSONResponse(content=segmented_image, status_code=400)
segmented_image = segmented_image.resize((224, 224))
detection_results = await detect_pieces(segmented_image)
if "error" in detection_results:
return JSONResponse(content=detection_results, status_code=400)
fen = gen_fen(detection_results, perspective)
if not fen:
return JSONResponse(content={"error": "FEN generation failed", "details": "Invalid input data"}, status_code=500)
return JSONResponse(content={"FEN": fen}, status_code=200)
except Exception as e:
return JSONResponse(content={"error": "Unexpected error occurred", "details": str(e)}, status_code=500)
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