Deploy hyper3labs/HyperView from Hyper3Labs/hyperview-spaces@dbde661

Dockerfile

@@ -21,14 +21,14 @@ WORKDIR $HOME/app
 
 RUN pip install --upgrade pip
 
-ARG HYPERVIEW_VERSION=0.4.2
-ARG HYPER_MODELS_VERSION=0.2.0
+ARG HYPERVIEW_VERSION=0.6.2
+ARG HYPER_MODELS_VERSION=0.3.0
 
 # Install CPU-only PyTorch first so the Space does not pull the default CUDA bundle,
 # then pin released HyperView packages so Docker cache cannot hold an older release.
 RUN pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
 RUN pip install "hyperview==${HYPERVIEW_VERSION}" && python -c "import hyperview; print('hyperview', hyperview.__version__)"
-RUN pip install "hyper-models==${HYPER_MODELS_VERSION}" && python -c "import hyper_models; print('hyper_models', hyper_models.__version__)"
+RUN pip install "hyper-models[ml]==${HYPER_MODELS_VERSION}" && python -c "import hyper_models; print('hyper_models', hyper_models.__version__)"
 
 COPY --chown=user demo.py ./demo.py
 

README.md

@@ -25,8 +25,8 @@ rights holder.
 
 The Docker image installs released packages from PyPI:
 
-- `hyperview==0.4.2`
-- `hyper-models==0.2.0`
+- `hyperview==0.6.2`
+- `hyper-models[ml]==0.3.0`
 
 ## Dataset
 

demo.py

@@ -12,6 +12,7 @@ from datasets import load_dataset
 from PIL import Image, ImageOps
 
 import hyperview as hv
+from hyperview.core.sample import Sample
 
 SPACE_HOST = "0.0.0.0"
 SPACE_PORT = 7860
@@ -154,11 +155,13 @@ def add_inat24_samples(dataset: hv.Dataset) -> None:
         metadata["source_dataset"] = HF_DATASET
         metadata["sample_strategy"] = "stratified_by_inat24_supercategory"
 
-        dataset.add_image(
-            str(image_path),
-            label=group,
-            metadata=metadata,
-            sample_id=sample_id,
+        dataset.add_sample(
+            Sample(
+                id=sample_id,
+                filepath=str(image_path),
+                label=group,
+                metadata=metadata,
+            ),
         )
         counts[group] += 1
         existing_ids.add(sample_id)