Fix remote paths. Updated Dockerfile and build image action (#7)

.github/workflows/build_image.yml

@@ -4,28 +4,39 @@ on:
   workflow_dispatch:
     inputs:
       tag_version:
-        description: "Docker Image Tag"
+        description: 'Docker Image Tag (without "v")'  
         required: true
         default: ""
 
 jobs:
   docker:
     runs-on: ubuntu-latest
     steps:
+      - 
+        name: Free Disk Space (Ubuntu)
+        uses: jlumbroso/free-disk-space@main
+        with:
+          tool-cache: false
+          android: true
+          dotnet: true
+          haskell: true
+          large-packages: true
+          docker-images: false
+          swap-storage: true
       - name: Set up QEMU
-        uses: docker/setup-qemu-action@v2
+        uses: docker/setup-qemu-action@v3
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v2
+        uses: docker/setup-buildx-action@v3
       - name: Login to DockerHub
-        uses: docker/login-action@v2
+        uses: docker/login-action@v3
         with:
           username: ${{ secrets.DOCKERHUB_USERNAME }}
           password: ${{ secrets.DOCKERHUB_TOKEN }}
       - name: Get repository name
         run: echo "REPOSITORY_NAME=${GITHUB_REPOSITORY#*/}" >> $GITHUB_ENV
       - name: Build and push
-        uses: docker/build-push-action@v3
+        uses: docker/build-push-action@v5
         with:
           push: true
           file: docker/Dockerfile
-          tags: supervisely/${{ env.REPOSITORY_NAME }}:${{ github.event.inputs.tag_version }}
+          tags: supervisely/embeddings_app:${{ github.event.inputs.tag_version }}

_legacy/calculate_embeddings/src/main.py

@@ -319,7 +319,8 @@ def infer_one(image, labels, instance_mode):
         json.dump(cfg, f)
     torch.save(embeddings, save_paths["embeddings"])
     print("uploading to team_files...")
-    api.file.upload_bulk(team_id, list(save_paths.values()), list(save_paths.values()))
+    remote_paths = [f"/{p}" for p in list(save_paths.values())]
+    api.file.upload_bulk(team_id, list(save_paths.values()), remote_paths)
 
     print("result shape:", embeddings.shape)
     print("done")

_legacy/visualize_embeddings/src/main.py

@@ -100,7 +100,8 @@ def calculate_projections(projection_method, metric="euclidean", umap_min_dist=0
     )
     torch.save(projections, save_paths["projections"])
     print("uploading projections to team_files...")
-    api.file.upload(team_id, save_paths["projections"], save_paths["projections"])
+    remote_path = f"/{save_paths['projections']}"
+    api.file.upload(team_id, save_paths["projections"], remote_path)
 
 
 obj_classes = list(set(all_info["object_cls"]))

dev_requirements.txt

@@ -1,6 +1,6 @@
-supervisely
-transformers
-timm
+supervisely==6.72.134
+transformers==4.33.2
+timm==0.9.5
 torch
-scikit-learn
-umap-learn
+scikit-learn==1.3.1
+umap-learn==0.5.4

docker/Dockerfile

@@ -1,4 +1,9 @@
-FROM supervisely/clip_filtering:1.0.2
+FROM supervisely/base-py-sdk:6.73.90
+
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+RUN pip3 install torch==1.11.0+cu113 torchvision==0.12.0+cu113 --extra-index-url https://download.pytorch.org/whl/cu113
+
 
 RUN pip3 install transformers==4.33.2 timm==0.9.5 scikit-learn==1.3.1 umap-learn==0.5.4
-RUN pip3 install supervisely==6.72.134

src/main.py

@@ -359,11 +359,15 @@ def run():
             projections = run_utils.calculate_projections(embeddings, all_info_list, projection_method, metric=metric)
         print("uploading projections to team_files...")
         torch.save(projections, save_paths["projections"])
-        api.file.upload(team_id, save_paths["projections"], save_paths["projections"])
+        remote_path = f"/{save_paths['projections']}"
+        api.file.upload(team_id, save_paths["projections"], remote_path)
     file_id = str(api.file.get_info_by_path(team_id, "/" + save_paths["embeddings"]).id)
     server_address = os.environ.get("SERVER_ADDRESS")
     if server_address:
-        url = f"{server_address}/files/{file_id}"
+        if sly.is_development():
+            url = sly.utils.abs_url(f"files/{file_id}")
+        else:
+            url = f"/files/{file_id}"
         info_run.description += f"all was saved to team_files: <a href={url}>{save_paths['embeddings']}</a><br>"
 
     # 6. Show chart

src/run_utils.py

@@ -50,7 +50,8 @@ def upload_embeddings(embeddings, info_updated, cfg, api, path_prefix, save_path
     with open(save_paths["cfg"], "w") as f:
         json.dump(cfg, f)
     torch.save(embeddings, save_paths["embeddings"])
-    api.file.upload_bulk(team_id, list(save_paths.values()), list(save_paths.values()))
+    remote_paths = [f"/{p}" for p in list(save_paths.values())]
+    api.file.upload_bulk(team_id, list(save_paths.values()), remote_paths)
 
 
 def download_embeddings(api, path_prefix, save_paths, team_id):