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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
from pydantic import BaseModel
app = FastAPI()
class DetectionResults(BaseModel):
boxes: list
confidences: list
classes: list
class FenRequest(BaseModel):
detections: DetectionResults
perspective: str
@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(request: FenRequest):
results = request.detections
perspective = request.perspective
try:
if perspective not in ["w", "b"]:
return JSONResponse(
content={"error": "Perspective must be 'w' (white) or 'b' (black)"},
status_code=400
)
if not results.boxes or not results.confidences or not results.classes:
return JSONResponse(
content={"error": "Invalid input", "details": "Missing required fields"},
status_code=400
)
print(results.model_dump())
fen = gen_fen(results.model_dump(), 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
) |