wrong name for notebook

MouseLand · Jan 11, 2023 · 076e5c8 · 076e5c8
1 parent ca01558
commit 076e5c8
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Showing 2 changed files with 21 additions and 1,105 deletions.
diff --git a/notebooks/run_cellpose_2.0.ipynb b/notebooks/run_cellpose_2.0.ipynb
diff --git a/notebooks/run_cellpose_2.ipynb b/notebooks/run_cellpose_2.ipynb
@@ -4,9 +4,7 @@
   "metadata": {
     "accelerator": "GPU",
     "colab": {
-      "name": "run_cellpose_2.0.ipynb",
       "provenance": [],
-      "collapsed_sections": [],
       "include_colab_link": true
     },
     "kernelspec": {
@@ -25,7 +23,8 @@
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
       "version": "3.8.10"
-    }
+    },
+    "gpuClass": "standard"
   },
   "cells": [
     {
@@ -35,7 +34,7 @@
         "colab_type": "text"
       },
       "source": [
-        "<a href=\"https://colab.research.google.com/github/MouseLand/cellpose/blob/main/notebooks/run_cellpose_2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+        "<a href=\"https://colab.research.google.com/github/MouseLand/cellpose/blob/main/notebooks/run_cellpose_2.0.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
@@ -101,7 +100,7 @@
         "!pip install \"opencv-python-headless<4.3\"\n",
         "!pip install cellpose"
       ],
-      "execution_count": 1,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -168,7 +167,7 @@
         "yn = ['NO', 'YES']\n",
         "print(f'>>> GPU activated? {yn[use_GPU]}')"
       ],
-      "execution_count": 2,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -292,7 +291,7 @@
         "id": "EMG3YYFSdieb",
         "outputId": "d0ef685b-fbda-445c-e882-a53136794934"
       },
-      "execution_count": 3,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -363,7 +362,7 @@
         "    plt.imshow(masks)\n",
         "    plt.axis('off')\n"
       ],
-      "execution_count": 7,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "display_data",
@@ -494,7 +493,7 @@
         "id": "XQI4aUxCjz3n",
         "outputId": "804d0459-b120-4298-9b4c-87a9ca26401c"
       },
-      "execution_count": 8,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -530,7 +529,7 @@
         "id": "mQsv-Iz7m_CF",
         "outputId": "bef9d0e1-ca51-450c-8c60-856c3f545bdb"
       },
-      "execution_count": 12,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -589,7 +588,7 @@
         "# diameter of labels in training images\n",
         "diam_labels = model.diam_labels.copy()"
       ],
-      "execution_count": 11,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -691,7 +690,7 @@
         "id": "_0AGsH5p6K6S",
         "outputId": "3f67063a-2197-4ec2-8619-0b52c98fd0ee"
       },
-      "execution_count": 14,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -754,7 +753,7 @@
         "id": "Z2ac5gtr-HPq",
         "outputId": "65c96437-85e4-42cf-8d4b-414b6ba98c0a"
       },
-      "execution_count": 15,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "display_data",
@@ -838,7 +837,7 @@
         "cellView": "form",
         "id": "vDu4Ixjo588O"
       },
-      "execution_count": 16,
+      "execution_count": null,
       "outputs": []
     },
     {
@@ -870,7 +869,7 @@
         "id": "InyKGtD3D2ZX",
         "outputId": "b1b4ecf3-41a0-4463-8944-afd8200cece0"
       },
-      "execution_count": 17,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -905,7 +904,7 @@
         "run_str = f'python -m cellpose --use_gpu --verbose --dir {dir} --pretrained_model {model_path} --chan {chan} --chan2 {chan2} --diameter {diameter} --flow_threshold {flow_threshold} --cellprob_threshold {cellprob_threshold}'\n",
         "print(run_str)"
       ],
-      "execution_count": 18,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -957,7 +956,7 @@
         "id": "gCcbs722BYd0",
         "outputId": "b7de466b-4e7a-4585-b1d7-c282593b3fab"
       },
-      "execution_count": 19,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -1002,9 +1001,9 @@
         "                      flows, \n",
         "                      diameter*np.ones(len(masks)), \n",
         "                      files, \n",
-        "                      channels)"
+        "                      [chan, chan2])"
       ],
-      "execution_count": 20,
+      "execution_count": null,
       "outputs": []
     },
     {
@@ -1023,7 +1022,7 @@
         "              masks, \n",
         "              flows, \n",
         "              files, \n",
-        "              channels=channels,\n",
+        "              channels=[chan, chan2],\n",
         "              png=True, # save masks as PNGs and save example image\n",
         "              tif=True, # save masks as TIFFs\n",
         "              save_txt=True, # save txt outlines for ImageJ\n",
@@ -1035,7 +1034,7 @@
       "metadata": {
         "id": "Da-Rtx09DEZB"
       },
-      "execution_count": 21,
+      "execution_count": null,
       "outputs": []
     },
     {
@@ -1054,7 +1053,7 @@
         "id": "PiP9MWN4F3Sx",
         "outputId": "e70088bf-dbb2-4b49-a5df-620c2b253d68"
       },
-      "execution_count": 22,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "execute_result",