changed imports

api/Dockerfile

@@ -12,7 +12,8 @@ COPY requirements.txt .
 
 RUN pip install --no-cache-dir -r requirements.txt
 
-COPY . .
+COPY src .
+COPY start_server.sh .
 
 RUN chmod +x start_server.sh
 

api/src/r_cnn/r_cnn_test.py

@@ -1,21 +1,12 @@
-import json
 import os
-import cv2
-from matplotlib import pyplot as plt
-import numpy as np
 from torch import tensor
 import torch
 from torch.utils.data import DataLoader
-from torchvision import transforms
+from torchvision.transforms import ToTensor
-from torchvision.transforms import ToTensor, functional
-import torchvision.transforms.functional as TF
-from tqdm import tqdm
 import torch.nn as nn
-import torch.nn.functional as F
 
 from .r_cnn import ObjectDetectionCNN, train, eval
 from .cocoDetectionDataset import CocoDetectionDataset
-import random
 
 SAVE_PATH = "./saved_models"
 PADDING = 20

api/src/server.py

@@ -80,6 +80,7 @@ async def predict(file: UploadFile = File(...)):
 
 load_dotenv("../database/.env")
 API_KEY = os.getenv("API_KEY")
+DATABASE = "../database/reviews.db"
 
 def get_api_key(authorization: str = Header(None)):
     if authorization != f"Bearer {API_KEY}":
@@ -98,7 +99,7 @@ sem_db = threading.Semaphore(1)
 def get_reviews(auth=Depends(get_api_key)):
     with sem_db:
         conn = sqlite3.connect(
-            "database/reviews.db",
+            DATABASE,
             check_same_thread=False
         )
         cur = conn.cursor()
@@ -118,7 +119,7 @@ def get_reviews(auth=Depends(get_api_key)):
 def post_review(review: Review):
     with sem_db:
         conn = sqlite3.connect(
-            "database/reviews.db",
+            DATABASE,
             check_same_thread=False
         )
         cur = conn.cursor()
@@ -136,7 +137,7 @@ def post_review(review: Review):
 def delete_review(auth=Depends(get_api_key)):
     with sem_db:
         conn = sqlite3.connect(
-            "database/reviews.db",
+            DATABASE,
             check_same_thread=False
         )
         cur = conn.cursor()

api/src/util.py

@@ -1,5 +1,3 @@
-from PIL import Image
-import os
 from matplotlib import pyplot as plt
 import torch
 
@@ -26,7 +24,6 @@ def visualizeData(dataset):
     for i in range(4):
         img = images[i]
 
-        # Convert tensor shape from [C,H,W] -> [H,W,C]
         img = img.permute(1, 2, 0)
 
         plt.figure(figsize=(3,3))

api/start_server.sh

@@ -1 +1 @@
-uvicorn server:app --host 0.0.0.0 --port 8000 --reload
+uvicorn src/server:app --host 0.0.0.0 --port 8000 --reload