feat: new server

.github/workflows/docker-publish-prd.yaml

@@ -0,0 +1,59 @@
+name: Build and Push Docker Image
+
+on:
+  push:
+    branches: [ main ]
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Check out code
+      uses: actions/checkout@v3
+
+    - name: Create credentials.json
+      run: echo '${{ secrets.GCS_SERVICE_ACCOUNT_OLD }}' > $GITHUB_WORKSPACE/credentials.json
+
+    - name: Authenticate to Google Cloud
+      uses: google-github-actions/auth@v2
+      with:
+        credentials_json: ${{ secrets.GCP_SERVICE_ACCOUNT }}
+
+    - name: "Set up Cloud SDK"
+      uses: "google-github-actions/setup-gcloud@v1"
+      with:
+        project_id: "healthy-highway-293513"
+        service_account_key: ${{ secrets.GCP_SERVICE_ACCOUNT }}
+        version: "latest"
+
+    - name: "Use gcloud CLI"
+      run: "gcloud info"
+
+    - name: "Download .env from GCS"
+      run: |
+        gsutil cp gs://action-envs/luzia-api.env ./.env
+
+    - name: "Docker auth"
+      run: |-
+        gcloud auth configure-docker us-central1-docker.pkg.dev --quiet
+    
+    - name: Build image
+      run: docker build . --file ./infra/Dockerfile --tag us-central1-docker.pkg.dev/healthy-highway-293513/eagle-spirit/eagle:luzia-api-${{ github.sha }}
+
+    - name: Push image
+      run: docker push us-central1-docker.pkg.dev/healthy-highway-293513/eagle-spirit/eagle:luzia-api-${{ github.sha }}
+
+    - name: Update GitOps Repo
+      run: |
+        # Clone your GitOps repo #
+        git clone https://${{ secrets.PAT }}@github.com/eagle-spirit/deployment.git
+        # Change to the directory containing your manifests
+        cd deployment/luzia-api
+        # Replace the image tag in your manifests
+        sed -i "s/luzia-api-[0-9a-f]\{40\}/luzia-api-${{ github.sha }}/g" deployment.yaml
+        # Commit and push the changes to GitHub
+        git config --global user.email "[email protected]"
+        git config --global user.name "Gabriel Aranha"
+        git commit -am "Update image tag to luzia-api-${{ github.sha }}"
+        git push

.gitignore

@@ -182,3 +182,4 @@ results/*
 models/*
 custom_metrics.py
 app/credentials/*.json
+credentials.json

app/models.py

@@ -1,5 +1,6 @@
 import base64
-import io, os
+import io
+import os
 
 import cv2
 import matplotlib.cm as cm
@@ -10,14 +11,13 @@
 from IPython.display import Image
 from PIL import Image
 from tensorflow import keras
-
 from utilities import cam_models
 
 
 def save_heatmap(heatmap, output_path="heatmap.png"):
-    plt.imshow(heatmap, cmap='jet')
-    plt.axis('off')
-    plt.savefig(output_path, bbox_inches='tight', pad_inches=0)
+    plt.imshow(heatmap, cmap="jet")
+    plt.axis("off")
+    plt.savefig(output_path, bbox_inches="tight", pad_inches=0)
 
 
 def preprocess_image(image: Image.Image) -> np.ndarray:
@@ -27,31 +27,39 @@ def preprocess_image(image: Image.Image) -> np.ndarray:
     image_array = np.expand_dims(image_array, axis=0)
     return image_array
 
+
 def load_model_from_gcs(bucket_name: str, model_path: str):
-    os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "./app/credentials/credentials.json"
+    os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "./credentials/credentials.json"
+    print(f"Downloading model from {bucket_name}/{model_path}")
     storage_client = storage.Client()
     bucket = storage_client.get_bucket(bucket_name)
     blob = storage.Blob(model_path, bucket)
     local_model_path = f"/tmp/{model_path}"
     blob.download_to_filename(local_model_path)
     return cam_models.load_saved_model(local_model_path)
 
+
 def evaluate_model(model, image_array: np.ndarray):
     prediction = model.predict(image_array)
     return prediction
 
+
 def superimpose_gradcam(image_path, heatmap, alpha=0.4, cam_path="cam.jpg"):
     # Load the original image
     original_img = cv2.imread(image_path)
     # resize the original image to the size of the heatmap
     original_img = cv2.resize(original_img, (299, 299))
-    original_img = np.clip(original_img, 0, 255).astype(np.uint8)  # Ensure values are still in the range [0, 255]
+    original_img = np.clip(original_img, 0, 255).astype(
+        np.uint8
+    )  # Ensure values are still in the range [0, 255]
 
     heatmap1 = heatmap - np.min(heatmap)
     heatmap1 = heatmap1 / np.ptp(heatmap1)
 
     # Rescale heatmap to a range 0-255
-    heatmap1 = np.uint8(255 * cv2.resize(heatmap1, (original_img.shape[0], original_img.shape[1])))
+    heatmap1 = np.uint8(
+        255 * cv2.resize(heatmap1, (original_img.shape[0], original_img.shape[1]))
+    )
 
     # Use jet colormap to colorize heatmap
     jet = cm.get_cmap("jet")
@@ -65,7 +73,7 @@ def superimpose_gradcam(image_path, heatmap, alpha=0.4, cam_path="cam.jpg"):
     jet_heatmap = keras.preprocessing.image.img_to_array(jet_heatmap)
 
     superimposed_img = jet_heatmap * alpha + original_img
-    #superimposed_img = (jet_heatmap * alpha) + (original_img * (1 - alpha))
+    # superimposed_img = (jet_heatmap * alpha) + (original_img * (1 - alpha))
 
     # Ensure the resulting image is still in the range [0, 255]
     superimposed_img = np.clip(superimposed_img, 0, 255).astype(np.uint8)
@@ -75,7 +83,7 @@ def superimpose_gradcam(image_path, heatmap, alpha=0.4, cam_path="cam.jpg"):
     # Save the superimposed image in JPEG format
     with io.BytesIO() as buffer:
         img_pil = keras.preprocessing.image.array_to_img(superimposed_img_rgb)
-        img_pil.save(buffer, format='JPEG')
+        img_pil.save(buffer, format="JPEG")
         buffer.seek(0)
         superimposed_image = buffer.getvalue()
 

infra/Dockerfile

@@ -29,22 +29,18 @@ ENV LANG pt_BR.UTF-8 \
   LC_ALL pt_BR.UTF-8
 
 # COPY EVERYTING FROM THE CURRENT DIRECTORY TO THE WORKDIR
-COPY ./pyproject.toml ./
-COPY ./poetry.lock ./
-COPY ./app/ ./app
-COPY ./app/boot.sh ./app/boot.sh
-COPY ./.env ./app/.env
+COPY ./pyproject.toml ./poetry.lock ./app/ ./app/boot.sh ./.env /home/$USER/app/
+COPY ./credentials.json /home/$USER/app/credentials/
 
-# Create .env file
-RUN printenv | grep -v "no_proxy" >> ./app/.env
+WORKDIR /home/$USER/app
 
 RUN poetry install
 
-RUN chmod +x ./app/boot.sh
+RUN chmod +x ./boot.sh
 
 RUN chown -R $USER:$USER /home/$USER
 USER $USER
 
-WORKDIR /home/$USER/app
+
 
 ENTRYPOINT ["sh", "./boot.sh"]