Add huggingface segmentation models (#254)

* add huggingface-segmentation * increment version * update to not use allow_install * segmentation testing notebook * fiddling * rename and simplify segmentation notebook WIP * change bad notebook cells * rename example notebook * rename segmentation notebook
alan-turing-institute · May 25, 2022 · 92bf9ff · 92bf9ff
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diff --git a/examples/scivision-core-functionality.ipynb → ...se scivision (image classification).ipynb b/examples/scivision-core-functionality.ipynb → ...se scivision (image classification).ipynb
@@ -150,53 +150,18 @@
    "source": [
     "## Loading the model\n",
     "\n",
-    "Some model entries in the scivision catalog contain a single loadable model. Here, let's load the \"image-classifiers\" entry, which contains each of the models in the [image-classifiers](https://pypi.org/project/image-classifiers/) package. We can do this with the `load_pretrained_model` function. We'll load 2 models (\"resnet18\" and \"densenet121\"), making sure to set the `allow_install` arg to True the first time `load_pretrained_model` is called (note the \"model\" arg is not mandatory and will have a default value for any model catalog entries that have more than one model - for model catalog entries with a single model, this need not be set):"
+    "Some model entries in the scivision catalog contain a single loadable model. Here, let's load the \"image-classifiers\" entry, which contains each of the models in the [image-classifiers](https://pypi.org/project/image-classifiers/) package. We can do this with the `load_pretrained_model` function. We'll load 2 models (`resnet18` and `densenet121`).\n",
+    "\n",
+    "Note: the \"model\" arg is not mandatory and will have a default value for any model catalog entries that have more than one model - for model catalog entries with a single model, this need not be set:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Collecting scivision_classifier\n",
-      "  Cloning https://github.com/alan-turing-institute/scivision_classifier (to revision main) to /private/var/folders/kf/72snt1z56h56smb3y7c0dxpr9rwb6q/T/pip-install-12ttdzvt/scivision-classifier_7004fcecb5334c47b6cb2eae4803b6c3\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "  Running command git clone --filter=blob:none --quiet https://github.com/alan-turing-institute/scivision_classifier /private/var/folders/kf/72snt1z56h56smb3y7c0dxpr9rwb6q/T/pip-install-12ttdzvt/scivision-classifier_7004fcecb5334c47b6cb2eae4803b6c3\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "  Resolved https://github.com/alan-turing-institute/scivision_classifier to commit 9ae8cd11232ffd1bddcbcb0a7bbf1172028570ef\n",
-      "  Preparing metadata (setup.py): started\n",
-      "  Preparing metadata (setup.py): finished with status 'done'\n",
-      "Building wheels for collected packages: scivision_classifier\n",
-      "  Building wheel for scivision_classifier (setup.py): started\n",
-      "  Building wheel for scivision_classifier (setup.py): finished with status 'done'\n",
-      "  Created wheel for scivision_classifier: filename=scivision_classifier-0.0.1-py3-none-any.whl size=3883 sha256=4fc051cf088067bf79e11d01db304d4e002e7a663284ea549a5cb039ad4f1521\n",
-      "  Stored in directory: /private/var/folders/kf/72snt1z56h56smb3y7c0dxpr9rwb6q/T/pip-ephem-wheel-cache-7_rxr2ez/wheels/af/27/f9/5c32ecec2f2682373da54294d060008ca1d046e18d74187784\n",
-      "Successfully built scivision_classifier\n",
-      "Installing collected packages: scivision_classifier\n",
-      "  Attempting uninstall: scivision_classifier\n",
-      "    Found existing installation: scivision-classifier 0.0.1\n",
-      "    Uninstalling scivision-classifier-0.0.1:\n",
-      "      Successfully uninstalled scivision-classifier-0.0.1\n",
-      "Successfully installed scivision_classifier-0.0.1\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "resnet_model = load_pretrained_model(model_repo, allow_install=True, model='resnet18')\n",
+    "resnet_model = load_pretrained_model(model_repo, model='resnet18')\n",
     "densenet_model = load_pretrained_model(model_repo, model='densenet121')"
    ]
   },
@@ -920,7 +885,7 @@
        "Coordinates:\n",
        "  * y        (y) int64 0 1 2 3 4 5 6 7 8 ... 231 232 233 234 235 236 237 238 239\n",
        "  * x        (x) int64 0 1 2 3 4 5 6 7 8 ... 253 254 255 256 257 258 259 260 261\n",
-       "  * channel  (channel) int64 0 1 2</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 240</li><li><span class='xr-has-index'>x</span>: 262</li><li><span class='xr-has-index'>channel</span>: 3</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1ae1e7de-8d49-4043-b4bd-6dbfd025764c' class='xr-array-in' type='checkbox' checked><label for='section-1ae1e7de-8d49-4043-b4bd-6dbfd025764c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(240, 262, 3), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "  * channel  (channel) int64 0 1 2</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 240</li><li><span class='xr-has-index'>x</span>: 262</li><li><span class='xr-has-index'>channel</span>: 3</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fdb4719e-8aab-437f-891e-565e35b5e4aa' class='xr-array-in' type='checkbox' checked><label for='section-fdb4719e-8aab-437f-891e-565e35b5e4aa' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(240, 262, 3), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
        "            <table>\n",
@@ -1000,7 +965,7 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-06aeccac-5369-4c0d-bc99-ebe58a07c921' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06aeccac-5369-4c0d-bc99-ebe58a07c921' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 235 236 237 238 239</div><input id='attrs-6ae8ece5-8f0f-4b02-b0b7-7179346dc4ce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ae8ece5-8f0f-4b02-b0b7-7179346dc4ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-773e4854-4a7a-44d1-9b16-711256c2696e' class='xr-var-data-in' type='checkbox'><label for='data-773e4854-4a7a-44d1-9b16-711256c2696e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 237, 238, 239])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 257 258 259 260 261</div><input id='attrs-db6f1784-257f-4591-b5e8-f2fb52e6516a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db6f1784-257f-4591-b5e8-f2fb52e6516a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aff686c4-e173-4024-85f8-c97554bd5ce2' class='xr-var-data-in' type='checkbox'><label for='data-aff686c4-e173-4024-85f8-c97554bd5ce2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 259, 260, 261])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-19fda842-f299-4283-add5-8c7df15f1e01' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-19fda842-f299-4283-add5-8c7df15f1e01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af751093-a408-46a4-9ec7-c0cf85624483' class='xr-var-data-in' type='checkbox'><label for='data-af751093-a408-46a4-9ec7-c0cf85624483' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6fbbf13f-1245-4cea-a8d9-bd6b83a9b34c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6fbbf13f-1245-4cea-a8d9-bd6b83a9b34c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "</table></div></div></li><li class='xr-section-item'><input id='section-27da3ffc-3f0a-4107-b297-345844ca77bc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-27da3ffc-3f0a-4107-b297-345844ca77bc' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 235 236 237 238 239</div><input id='attrs-1780b9b5-7e84-468a-8211-24e23f1a81a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1780b9b5-7e84-468a-8211-24e23f1a81a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-756a69e6-e7a1-451b-849e-be6b25bd37d5' class='xr-var-data-in' type='checkbox'><label for='data-756a69e6-e7a1-451b-849e-be6b25bd37d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 237, 238, 239])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 257 258 259 260 261</div><input id='attrs-bae0823f-7d6a-4240-b9f5-1edd2325d445' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bae0823f-7d6a-4240-b9f5-1edd2325d445' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6ae0d9a-e6d6-478a-bf12-bf88c6e76d21' class='xr-var-data-in' type='checkbox'><label for='data-d6ae0d9a-e6d6-478a-bf12-bf88c6e76d21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 259, 260, 261])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-fb1dd320-738d-433a-9f21-354600f8be47' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fb1dd320-738d-433a-9f21-354600f8be47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db9a335d-ef6f-4b36-af5e-0f3164420ec6' class='xr-var-data-in' type='checkbox'><label for='data-db9a335d-ef6f-4b36-af5e-0f3164420ec6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f2a4c119-969c-45cc-af0e-50541ca1fddd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f2a4c119-969c-45cc-af0e-50541ca1fddd' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (y: 240, x: 262, channel: 3)>\n",
@@ -1045,7 +1010,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x167182a00>"
+       "<matplotlib.image.AxesImage at 0x173c761f0>"
       ]
      },
      "execution_count": 13,
@@ -1083,6 +1048,13 @@
    "execution_count": 14,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1/1 [==============================] - 0s 371ms/step\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -1103,6 +1075,13 @@
    "execution_count": 15,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1/1 [==============================] - 2s 2s/step\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -1346,42 +1325,6 @@
    "execution_count": 17,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Collecting scivision_huggingface\n",
-      "  Cloning https://github.com/alan-turing-institute/scivision_huggingface (to revision main) to /private/var/folders/kf/72snt1z56h56smb3y7c0dxpr9rwb6q/T/pip-install-56tpd_1p/scivision-huggingface_5812e68de5c54f73889ae7ce50486097\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "  Running command git clone --filter=blob:none --quiet https://github.com/alan-turing-institute/scivision_huggingface /private/var/folders/kf/72snt1z56h56smb3y7c0dxpr9rwb6q/T/pip-install-56tpd_1p/scivision-huggingface_5812e68de5c54f73889ae7ce50486097\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "  Resolved https://github.com/alan-turing-institute/scivision_huggingface to commit 16df12f6872876b1b22ea45a3a2f33dd42091087\n",
-      "  Preparing metadata (setup.py): started\n",
-      "  Preparing metadata (setup.py): finished with status 'done'\n",
-      "Building wheels for collected packages: scivision_huggingface\n",
-      "  Building wheel for scivision_huggingface (setup.py): started\n",
-      "  Building wheel for scivision_huggingface (setup.py): finished with status 'done'\n",
-      "  Created wheel for scivision_huggingface: filename=scivision_huggingface-0.0.1-py3-none-any.whl size=3817 sha256=8a036189b9f92358eb27bc1709617dbc35a27fdbe70256d558960867597e0c4d\n",
-      "  Stored in directory: /private/var/folders/kf/72snt1z56h56smb3y7c0dxpr9rwb6q/T/pip-ephem-wheel-cache-p3bnj_5g/wheels/58/43/19/be5a260399f14abe94dbcffed3df890b92e52dc026f56e3ec2\n",
-      "Successfully built scivision_huggingface\n",
-      "Installing collected packages: scivision_huggingface\n",
-      "  Attempting uninstall: scivision_huggingface\n",
-      "    Found existing installation: scivision-huggingface 0.0.1\n",
-      "    Uninstalling scivision-huggingface-0.0.1:\n",
-      "      Successfully uninstalled scivision-huggingface-0.0.1\n",
-      "Successfully installed scivision_huggingface-0.0.1\n"
-     ]
-    },
     {
      "name": "stderr",
      "output_type": "stream",
@@ -1393,7 +1336,7 @@
    ],
    "source": [
     "huggingface_repo = models_catalog[models_catalog.name == \"huggingface-classifiers\"].url.item()\n",
-    "microsoft_model = load_pretrained_model(huggingface_repo, allow_install=True, model='microsoft_swin_tiny_patch4_window7_224')"
+    "microsoft_model = load_pretrained_model(huggingface_repo, model='microsoft_swin_tiny_patch4_window7_224')"
    ]
   },
   {