api_server.py: moved from frontend/main.py, made roughly functional

api_server.py

@@ -1,6 +1,7 @@
+from io import BytesIO
 from typing import Optional
 
-from fastapi import FastAPI
+from fastapi import FastAPI, File, UploadFile
 from pydantic import BaseModel
 
 import numpy as np
@@ -8,7 +9,9 @@ from cv2 import cv2
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from ..nets import Model
+from nets import Model
+from PIL import Image
+
 
 
 app = FastAPI()
@@ -23,11 +26,6 @@ app = FastAPI()
 #       kommt ctd überhaupt mit was anderem klar?
 
 
-class Item(BaseModel):
-    name: str
-    price: float
-    is_offer: Optional[bool] = None
-
 
 class IrImage(BaseModel):
     image: np.array
@@ -96,16 +94,18 @@ def inference_ctd(left, right, model, n_iter=20):
 
 
 @app.put("/ir")
-def read_ir_input(ir_image: IrImage):
+async def read_ir_input(file: UploadFile = File(...)):
-    pred_disp = inference_ctd(ir_image.image, reference_pattern)
+    try:
+        img = np.array(Image.open(BytesIO(await file.read())))
+    except Exception as e:
+        return {'error': 'couldn\'t read file', 'exception': e}
+    print(img.shape)
+    if len(img.shape) == 2:
+        img = np.stack((img for _ in range(3)))
+    pred_disp = inference_ctd(np.array(img), reference_pattern, None)
     return {"pred_disp": pred_disp}
 
 
-@app.get("/items/{item_id}")
+@app.get('/')
-def read_item(item_id: int, q: Optional[str] = None):
+def main():
-    return {"item_id": item_id, "q": q}
+    return {'test': 'abc'}
-
-
-@app.put("/items/{item_id}")
-def update_item(item_id: int, item: Item):
-    return {"item_price": item.price, "item_id": item_id}