Add task queue

.github/workflows/build-deploy-docker.yml

@@ -12,62 +12,35 @@ env:
   GITLAB_REGISTRY_TOKEN: ${{ secrets.GITLAB_REGISTRY_TOKEN }}
 
 jobs:
-  build-gateway:
-    runs-on: ubuntu-20.04
-    steps:
-      - name: Check out repo.
-        uses: actions/checkout@v4
-      - name: Setup buildx
-        run:  docker buildx create --use
-      - name: Sign in to segmentation gitlab registry.
-        run: echo "$GITLAB_REGISTRY_TOKEN" | docker login registry.gitlab.com -u "$GITLAB_REGISTRY_USERNAME" --password-stdin
-      - name: Build gateway image.
-        run: |
-          docker buildx build \
-            --platform linux/arm64 \
-            --tag registry.gitlab.com/segmentation964330/service/gateway \
-            --push \
-            ./gateway
-  build-nginx:
-    runs-on: ubuntu-20.04
-    steps:
-      - name: Check out repo.
-        uses: actions/checkout@v4
-      - name: Setup buildx
-        run:  docker buildx create --use
-      - name: Sign in to segmentation gitlab registry.
-        run: echo "$GITLAB_REGISTRY_TOKEN" | docker login registry.gitlab.com -u "$GITLAB_REGISTRY_USERNAME" --password-stdin
-      - name: Build nginx image.
-        run: |
-          docker buildx build \
-            --platform linux/arm64 \
-            --tag registry.gitlab.com/segmentation964330/service/nginx \
-            --push \
-            ./nginx
   deploy:
     runs-on: ubuntu-20.04
-    needs: [build-gateway, build-nginx]
     steps:
       - name: Check out repo.
         uses: actions/checkout@v4
-      - name: Copy docker compose file to OCI.
+      - name: Copy directory to OCI.
         uses: appleboy/[email protected]
         with:
           host: ${{ secrets.ORACLE_HOST }}
           username: ${{ secrets.ORACLE_USERNAME }}
           key: ${{ secrets.ORACLE_SSH_KEY }}
-          source: "./docker-compose.yml"
-          target: "."
+          source: "./"
+          target: "./SegmentationService"
       - name: Pull docker and deploy.
         uses: appleboy/[email protected]
         with:
           host: ${{ secrets.ORACLE_HOST }}
           username: ${{ secrets.ORACLE_USERNAME }}
           key: ${{ secrets.ORACLE_SSH_KEY }}
+          script_stop: true
           envs: GITLAB_REGISTRY_USERNAME, GITLAB_REGISTRY_TOKEN
           script: |
             echo "$GITLAB_REGISTRY_TOKEN" | docker login registry.gitlab.com -u "$GITLAB_REGISTRY_USERNAME" --password-stdin
-            sudo docker compose down
-            sudo docker compose pull
+            cd SegmentationService
+            sudo docker compose build
+            sudo docker compose push
+            sudo docker stop $(sudo docker ps -a -q)
+            sudo docker rm $(sudo docker ps -a -q)
             sudo docker compose up --detach
-            sudo docker image prune --force
+            sudo docker system prune --force
+            cd ..
+            rm -rf SegmentationService

.gitignore

@@ -1,2 +1 @@
 *.DS_Store
-artifacts

docker-compose.yml

@@ -1,13 +1,33 @@
 services:
+  redis:
+    container_name: redis
+    image: redis:7.0.15-alpine3.20
+    command: redis-server --bind redis --port 6379
+    tty: true
+    stdin_open: true
+  inference:
+    container_name: inference
+    image: registry.gitlab.com/segmentation964330/service/inference
+    build:
+      context: ./inference
+    volumes:
+      - ../artifacts/images:/home/artifacts/images
+      - ../artifacts/logs:/home/artifacts/logs
+      - ../artifacts/models:/home/artifacts/models
+    depends_on:
+      - redis
+    tty: true
+    stdin_open: true
   gateway:
     container_name: gateway
     image: registry.gitlab.com/segmentation964330/service/gateway
     build:
       context: ./gateway
     volumes:
-      - ./artifacts/images:/home/artifacts/images
-      - ./artifacts/logs:/home/artifacts/logs
-      - ./artifacts/models:/home/artifacts/models
+      - ../artifacts/images:/home/artifacts/images
+      - ../artifacts/logs:/home/artifacts/logs
+    depends_on:
+      - redis
     tty: true
     stdin_open: true
   nginx:

gateway/Dockerfile

@@ -1,4 +1,6 @@
-FROM registry.gitlab.com/segmentation964330/service/torchbase
+FROM python:3.12.4-alpine3.19
+
+WORKDIR /home
 
 COPY ./requirements.txt ./
 RUN pip install -r requirements.txt
@@ -8,9 +10,5 @@ COPY . .
 ENV WORKING_DIR="/home"
 ENV LOGS_DIR="/home/artifacts/logs/"
 ENV IMAGES_DIR="/home/artifacts/images/"
-ENV MODELS_DIR="/home/artifacts/models/"
-ENV SEGMENTATION_MODEL_NAME="pointrend_weights.pth"
-ENV CLASSIFICATION_MODEL_NAME="swinv2_weights.pth"
-ENV SPECIES_LIST="species.json"
 
 CMD ["gunicorn", "-c", "gunicorn_conf.py", "app:gunicorn_app"]

gateway/gunicorn_conf.py

@@ -1,6 +1,6 @@
 import os
 
-bind = '0.0.0.0:8000'
+bind = 'gateway:8000'
 accesslog = os.path.join(os.environ["LOGS_DIR"], 'gunicorn.log')
 errorlog = os.path.join(os.environ["LOGS_DIR"], 'gunicorn.log')
 workers = 1

gateway/requirements.txt

@@ -2,4 +2,6 @@ flask==3.0.3
 numpy==1.26.4
 pillow==10.4.0
 gunicorn==22.0.0
-flask-cors==4.0.1
+flask-cors==4.0.1
+redis==5.0.8
+rq==1.16.2

gateway/server/app.py

@@ -1,63 +1,54 @@
 import server.init
 server.init.init()
 
-from flask import Flask, request, jsonify, render_template
+from flask import Flask, request, jsonify
 from flask_cors import CORS
-from PIL import Image
+from PIL import Image, ImageOps
 import numpy as np
 import uuid
 import os
 import logging
 
-import server.classification as classification
-import server.segmentation as segmentation
-
-logger = logging.getLogger(__name__)
+from server.taskqueue import TaskQueue
 
 app = Flask(__name__)
 CORS(app)
-
-@app.route("/secretgui")
-def gui():
-    return render_template("hi.html")
+job_queue = TaskQueue("redis", "6379", "segmentation_queue")
+logger = logging.getLogger(__name__)
 
 @app.route("/healthcheck")
 def hello_world():
-    logger.info("Healthcheck.")
-    return "Hello world!", 200
+    logger.info("Healthcheck run.")
+    return "Hello world.", 200
 
-@app.route("/predict", methods=["POST"])
+@app.route("/upload", methods=["POST"])
 def predict():
     if 'file' not in request.files:
-        logger.info("Predict with no image.")
+        logger.info("Uploaded with no file.")
         return jsonify({'error': 'No file part in the request'}), 400
     file = request.files['file']
     try:
-        ip = request.environ['REMOTE_ADDR']
-        logger.info(f"Received image for {ip}.")
         image = Image.open(file.stream)
-        # Need to remove alpha channel.
-        if image.mode in ("RGBA", "P"):
-            image = image.convert("RGB")
-        try:
-            imgid = str(uuid.uuid1())
-            image.save(os.path.join(os.environ['IMAGES_DIR'], imgid + ".jpg"))
-            logger.info(f"Saved img as {imgid} - {ip}.")
-        except Exception as e:
-            logger.warn(f"Failed to save img: {imgid} - {str(e)} - {ip}")
-            print(e)
-        npimg = np.array(image)
-
-        logger.info(f"Starting segmentation for {imgid}.")
-        subimgs, base64s = segmentation.predict(npimg, 0.95)
-        logger.info(f"Finished segmentation: predicted {len(base64s)} pitchers for {imgid}.")
-
-        logger.info(f"Starting classification for {imgid}.")
-        for i, img in enumerate(subimgs):
-            base64s[i]['classification_preds'] = classification.predict(img)
-            logger.info(f"Predicted: {base64s[i]['classification_preds']} for {imgid}.")
-        logger.info(f"Finished classification for {imgid}.")
-
-        return jsonify(base64s), 200
+        image = image.convert("RGB")
+        image = ImageOps.exif_transpose(image)
+
+        img_and_job_id = str(uuid.uuid4())
+        imgname = img_and_job_id + '.jpg'
+        image.save(os.path.join(os.environ['IMAGES_DIR'], imgname))
+        logger.info(f"Saved image: {imgname}.")
+        job_id = job_queue.add_task("inference.infer", imgname, img_and_job_id)
+        return job_id, 200
     except Exception as e:
+        logger.error(f"Error in parsing and submitting image: {e}.")
         return jsonify({'error': str(e)}), 400
+
+@app.route("/status/<job_id>")
+def status(job_id):
+    try:
+        job_status, code = job_queue.get_job_status(job_id)
+    except Exception as e:
+        logger.warn(f"Unable to find job {job_id}: {str(e)}.")
+        return jsonify({'error': str(e)}), 404
+    if job_status['done']:
+        logger.info(f"Job {job_id} queried with finished status.")
+    return jsonify(job_status), code