Merge pull request #4 from fercer/dev-content

Development content

Author: fercer

README.md

@@ -24,20 +24,22 @@ Install the following packages in the newly created environment.
 ```
 conda activate scale-up
 
-conda install -c conda-forge "cellpose>=3.0,<4.0" tifffile=2025.6.11 "zarr>=2.0,<3.0" dask=2025.5.1 imagecodecs=2025.3.30
+conda install -c conda-forge "cellpose>=3.0,<4.0" tifffile=2025.6.11 "zarr>=2.0,<3.0" dask=2025.5.1 distributed=2025.5.1 dask-image=2024.5.3 imagecodecs=2025.3.30
 ```
 
-We might need to open some image files that are compressed using `JPEG2000`, to do that we'll use `imagecodecs` to have access to this compression algorithm.
+We'll open some image files that are compressed using `JPEG2000`, so we need `imagecodecs` to have access to this compression algorithm.
 
-Additionally, install Jupyterlab to follow the notebooks.
+Additionally, install Jupyterlab to follow the notebooks, and its Dask extension.
 
 ```
-conda activate scale-up
-
-conda install -c conda-forge jupyterlab=4.4.3
+conda install -c conda-forge jupyterlab=4.4.3 dask-labextension=7.0.0
 ```
 
 ## A test image
 
 We'll work with big microscopy images. An example of that kind of image can be found [here](https://openslide.cs.cmu.edu/download/openslide-testdata/Aperio/CMU-1.svs).
 So it is a good idea to have it downloaded as well.
+
+A crop of that image can be found [here](https://drive.google.com/file/d/17owNcq_Or6aBAyUVE33fyHSS0VvKuHSw/view?usp=sharing), along with its `Zarr` version [here](https://drive.google.com/file/d/1BmNxOrO3vOFPR-PCnV00DYgFsD1sDu47/view?usp=sharing).
+
+A smaller example image can be found [here](https://openslide.cs.cmu.edu/download/openslide-testdata/Aperio/CMU-1-Small-Region.svs), and its corresponding `Zarr` version is [here](https://drive.google.com/file/d/1MifgafB5mhVAvqjzEAAR_zQajAU5Dcya/view?usp=drive_link).

notebooks/Zarr_and_Dask_for_large-scale_imaging-Part-1.ipynb

@@ -605,7 +605,7 @@
    },
    "outputs": [],
    "source": [
-    "z_grp = tifffile.imread(\"CMU-1.svs\", aszarr=True)\n",
+    "z_grp = tifffile.imread(r\"C:\\Users\\Public\\Documents\\WSI_example\\CMU-1.svs\", aszarr=True)\n",
     "da_arr = da.from_zarr(z_grp, component=\"0\")"
    ]
   },
@@ -701,7 +701,7 @@
    },
    "outputs": [],
    "source": [
-    "da_sel = da_arr[10000:10000 + 2048, 10000:10000 + 2048]"
+    "da_sel = da_arr[16_000:16_000 + 2048, 8_000:8_000 + 2048]"
    ]
   },
   {
@@ -713,15 +713,6 @@
     "da_sel"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "da_sel.compute()"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -803,6 +794,15 @@
    "source": [
     "plt.imshow(arr_nuclei, cmap=\"gray\")"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.imshow(arr_nuclei[500:750, 250:500], cmap=\"gray\")"
+   ]
   }
  ],
  "metadata": {
@@ -811,7 +811,7 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "scale-up",
    "language": "python",
    "name": "python3"
   },