Feature/upload images background

backend/requirements.txt

@@ -6,6 +6,6 @@ python-multipart>=0.0.5
 gelf-formatter==0.2.1
 pyyaml>=5.4.1
 user-agents==2.2.0
-ua-parser
-python-openstackclient
-python-swiftclient
+ua-parser==0.10.0
+python-openstackclient==5.8.0
+python-swiftclient==4.0.0

backend/src/main.py

@@ -1,23 +1,27 @@
-import shutil
 import os
 import logging
 from logging.handlers import TimedRotatingFileHandler
 from datetime import datetime
 import time
 import json
-import asyncio
 from uuid import uuid4
 from typing import Union
-from fastapi import Request, Response, FastAPI, File, Form, UploadFile, HTTPException, Cookie
-from fastapi.responses import PlainTextResponse, FileResponse
+from fastapi import BackgroundTasks, Cookie, FastAPI, File, Form, HTTPException, Request, Response, UploadFile
+from fastapi.responses import PlainTextResponse
 from fastapi.middleware.cors import CORSMiddleware
 from gelfformatter import GelfFormatter
 from user_agents import parse
 import swiftclient
 from src.model import load_model_inference, predict_image
 
+
 CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
 
+CLOUD_PATH = f'https://storage.gra.cloud.ovh.net/v1/' + \
+    'AUTH_df731a99a3264215b973b3dee70a57af/basegun-public/' + \
+    f'uploaded-images/{os.environ["WORKSPACE"]}/'
+
+
 def init_variable(var_name: str, path: str) -> str:
     """Inits global variable for folder path
 
@@ -90,9 +94,6 @@ def setup_logs(log_dir: str) -> logging.Logger:
     allow_headers=["*"],
 )
 
-# Image storage
-PATH_IMGS = init_variable("PATH_IMGS", "../images")
-
 # Logs
 PATH_LOGS = init_variable("PATH_LOGS", "../logs")
 logger = setup_logs(PATH_LOGS)
@@ -119,6 +120,7 @@ def setup_logs(log_dir: str) -> logging.Logger:
     MODEL_VERSION = "-1"
 
 
+conn = None
 if "OS_USERNAME" in os.environ:
     # Connection to OVH cloud
     conn = swiftclient.Connection(
@@ -131,12 +133,12 @@ def setup_logs(log_dir: str) -> logging.Logger:
         },
         auth_version='3'
     )
-    CLOUD_PATH = f'https://storage.gra.cloud.ovh.net/v1/' + \
-    'AUTH_df731a99a3264215b973b3dee70a57af/basegun-public/' + \
-    f'uploaded-images/{os.environ["WORKSPACE"]}/'
     conn.get_account()
+else:
+    logger.warn('Variables necessary for OVH connection not set !')
 
-async def upload_image_ovh(content, img_name):
+
+def upload_image_ovh(content: bytes, img_name: str):
     """ Uploads an image to owh swift container basegun-public
         path uploaded-images/WORKSPACE/img_name
         where WORKSPACE is dev, preprod or prod
@@ -145,9 +147,39 @@ async def upload_image_ovh(content, img_name):
         content (bytes): file content
         img_name (str): name we want to give on ovh
     """
-    conn.put_object("basegun-public",
-                    f'uploaded-images/{os.environ["WORKSPACE"]}/{img_name}',
-                    contents=content)
+    num_tries = 0
+    LIMIT_TRIES = 5
+    image_path = os.path.join(CLOUD_PATH, img_name)
+    start = time.time()
+
+    if not conn:
+        logger.exception("Variables not set for using OVH swift.", extra={
+            "bg_error_type": "NameError"
+        })
+        return
+
+    while num_tries <= LIMIT_TRIES:
+        num_tries += 1
+        extras_logging = {
+            "bg_date": datetime.now().isoformat(),
+            "bg_upload_time": time.time()-start,
+            "bg_image_url": image_path
+        }
+        try:
+            conn.put_object("basegun-public",
+                            f'uploaded-images/{os.environ["WORKSPACE"]}/{img_name}',
+                            contents=content)
+            # if success, get out of the loop
+            logger.info("Upload to OVH successful", extra=extras_logging)
+            break
+        except Exception as e:
+            if (num_tries <= LIMIT_TRIES and e.__class__.__name__ == "ClientException"):
+                # we try uploading another time
+                time.sleep(30)
+                continue
+            else:
+                extras_logging["bg_error_type"] = e.__class__.__name__
+                logger.exception(e, extra=extras_logging)
 
 
 ####################
@@ -179,6 +211,7 @@ def logs():
 async def imageupload(
     request: Request,
     response: Response,
+    background_tasks: BackgroundTasks,
     image: UploadFile = File(...),
     date: float = Form(...),
     geolocation: str = Form(...),
@@ -209,18 +242,9 @@ async def imageupload(
         img_name = str(uuid4()) + os.path.splitext(image.filename)[1]
         img_bytes = image.file.read()
 
-        # save input image
-        if "OS_USERNAME" in os.environ:
-            # upload image to OVH Cloud
-            upload = asyncio.create_task(upload_image_ovh(img_bytes, img_name))
-            image_path = os.path.join(CLOUD_PATH, img_name)
-        else:
-            # save locally
-            logger.warn('Storing uploaded images locally in /tmp/basegun')
-            with open(os.path.join("/app/images/", img_name), "wb") as f:
-                f.write(img_bytes)
-            image_path = 'http://localhost:3000/temp/' + img_name
-
+        # upload image to OVH Cloud
+        background_tasks.add_task(upload_image_ovh, img_bytes, img_name)
+        image_path = os.path.join(CLOUD_PATH, img_name)
         extras_logging["bg_image_url"] = image_path
 
         # set user id
@@ -231,8 +255,7 @@ async def imageupload(
 
         # send image to model for prediction
         start = time.time()
-        prediction = asyncio.create_task(predict_image(model, img_bytes))
-        label, confidence = await prediction
+        label, confidence = predict_image(model, img_bytes)
         extras_logging["bg_label"] = label
         extras_logging["bg_confidence"] = confidence
         extras_logging["bg_model_time"] = round(time.time()-start, 2)
@@ -243,13 +266,10 @@ async def imageupload(
         else:
             extras_logging["bg_confidence_level"] = "high"
 
-        if "OS_USERNAME" in os.environ:
-            await upload
-
         logger.info("Identification request", extra=extras_logging)
 
         return {
-            "file": image_path,
+            "path": image_path,
             "label": label,
             "confidence": confidence,
             "confidence_level": extras_logging["bg_confidence_level"]

backend/src/model.py

@@ -5,7 +5,7 @@
 import torch
 import torchvision.models as Model
 from torchvision import transforms
-import time
+
 
 CLASSES = ['autre_epaule', 'autre_pistolet', 'epaule_a_levier_sous_garde',
         'epaule_a_percussion_silex', 'epaule_a_pompe', 'epaule_a_un_coup', 'epaule_a_verrou',
@@ -140,7 +140,7 @@ def prepare_input(image: Image) -> torch.Tensor:
     return image.unsqueeze(0).to(device)
 
 
-async def predict_image(model: Model, img: bytes) -> Union[str, float]:
+def predict_image(model: Model, img: bytes) -> Union[str, float]:
     """Run the model prediction on an image
 
     Args:

backend/tests/test_api.py

@@ -37,13 +37,14 @@ def test_upload_and_logs(self):
         res = r.json()
 
         # checks that the json result is as expected
-        self.assertEqual(set(res.keys()), set({"label", "confidence", "confidence_level", "file"}))
+        self.assertEqual(set(res.keys()), set({"label", "confidence", "confidence_level", "path"}))
         self.assertEqual(res["label"], "revolver")
         self.assertAlmostEqual(res["confidence"], 99.53, places=1)
         self.assertTrue(res["confidence_level"], "high")
+        self.assertTrue("ovh" in res["path"])
         # checks that written file is exactly the same as input file
-        self.assertTrue("ovh" in res["file"])
-        response = requests.get(res["file"])
+        time.sleep(30)
+        response = requests.get(res["path"])
         with Image.open(path) as image_one:
             with Image.open(BytesIO(response.content)) as image_two:
                 self.assertEqual(image_one.size, image_two.size)
@@ -52,7 +53,11 @@ def test_upload_and_logs(self):
         # checks that the result is written in logs
         r = requests.get(self.url + "/logs")
         self.assertEqual(r.status_code, 200)
-        log = r.json()[0]
+        # checks the latest log "Upload to OVH"
+        self.assertEqual(r.json()[0]["_bg_image_url"], r.json()[1]["_bg_image_url"])
+        self.assertEqual(r.json()[0]["short_message"], "Upload to OVH successful")
+        # checks the previous log "Identification request"
+        log = r.json()[1]
         self.assertEqual(
             set(log.keys()),
             set({'timestamp', '_bg_device', 'host', '_bg_model_time', 'version', '_bg_device_os', '_bg_device_family',

backend/tests/test_model.py

@@ -2,7 +2,6 @@
 import unittest
 import os
 import numpy as np
-import asyncio
 from PIL import Image
 from torch import Tensor
 from src.model import load_model_inference, prepare_input, \
@@ -50,6 +49,6 @@ def test_predict_image(self):
             os.path.dirname(os.path.abspath(__file__)),
             "revolver.jpg")
         with open(path, 'rb') as f:
-            res = asyncio.run(predict_image(self.model, f.read()))
+            res = predict_image(self.model, f.read())
         self.assertEqual(res[0], "revolver")
         self.assertAlmostEqual(res[1], 99.53, places=1)

docker-compose-dev.yml

@@ -13,7 +13,6 @@ services:
       target: ${BUILD_TARGET:-dev}
     container_name: basegun-backend
     environment:
-      - PATH_IMGS=/app/images
       - PATH_LOGS=/app/logs
       - OS_USERNAME
       - OS_PASSWORD
@@ -25,7 +24,6 @@ services:
     ports:
       - 5000:5000
     volumes:
-      - /tmp/basegun:/app/images
       - $PWD/backend/src:/app/src
       - $PWD/backend/tests:/app/tests
       - $PWD/backend/logs:/app/logs
@@ -44,6 +42,5 @@ services:
     ports:
       - 3000:3000
     volumes:
-      - /tmp/basegun:/app/public/temp
       - $PWD/frontend/src:/app/src
       - /app/node_modules

docker-compose-prod.yml

@@ -10,7 +10,6 @@ services:
       target: prod
     container_name: basegun-backend
     environment:
-      - PATH_IMGS=/app/images
       - PATH_LOGS=/app/logs
       - OS_USERNAME
       - OS_PASSWORD

frontend/package.json

@@ -1,6 +1,6 @@
 {
   "name": "basegun",
-  "version": "1.3.4",
+  "version": "1.3.5",
   "private": true,
   "scripts": {
     "serve": "vite preview",

frontend/src/components/ResultsComponent.vue

@@ -1,7 +1,7 @@
 <template>
     <div>
         <div class="result">
-            <div class="result-image" :style="{backgroundImage:`url(${store.imgName})`}"></div>
+            <div class="result-image" :style="{backgroundImage:`url(${store.img})`}"></div>
             <div class="fr-callout custom-callout">
                 <div v-if="store.confidence_level == 'low'">
                     <div class="callout-head">
@@ -109,7 +109,7 @@
             },
             sendFeedback(bool, event) {
                 const json = {
-                    "image_url": store.imgName,
+                    "image_url": store.imgUrl,
                     "feedback": bool,
                     "confidence": store.confidence,
                     "label": store.label,