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zjt committed 2023-10-21 21:55:27 +08:00
1 parent 6fdee8f272
commit 1c0e3e5fe7
31 files changed
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notebooks/automatic_mask_generator_example.ipynb
+38 -19
View File
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 10,
"id": "5fa21d44",
"metadata": {},
"outputs": [],
@@ -30,7 +30,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 11,
"id": "072e25b8",
"metadata": {},
"outputs": [
@@ -79,7 +79,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 12,
"id": "4fe300fb",
"metadata": {},
"outputs": [],
@@ -89,7 +89,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 13,
"id": "0685a2f5",
"metadata": {},
"outputs": [],
@@ -120,7 +120,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 14,
"id": "560725a2",
"metadata": {},
"outputs": [],
@@ -133,7 +133,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 15,
"id": "74b6e5f0",
"metadata": {},
"outputs": [],
@@ -164,7 +164,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 16,
"id": "ad354922",
"metadata": {},
"outputs": [],
@@ -175,13 +175,13 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 17,
"id": "e0ac8c67",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 2000x2000 with 1 Axes>"
]
@@ -215,10 +215,29 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 18,
"id": "1848a108",
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "AssertionError",
"evalue": "Torch not compiled with CUDA enabled",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mAssertionError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32me:\\Sam-test\\segment-anything\\notebooks\\automatic_mask_generator_example.ipynb 单元格 17\u001b[0m line \u001b[0;36m1\n\u001b[0;32m <a href='vscode-notebook-cell:/e%3A/Sam-test/segment-anything/notebooks/automatic_mask_generator_example.ipynb#X22sZmlsZQ%3D%3D?line=7'>8</a>\u001b[0m device \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mcuda\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m <a href='vscode-notebook-cell:/e%3A/Sam-test/segment-anything/notebooks/automatic_mask_generator_example.ipynb#X22sZmlsZQ%3D%3D?line=9'>10</a>\u001b[0m sam \u001b[39m=\u001b[39m sam_model_registry[model_type](checkpoint\u001b[39m=\u001b[39msam_checkpoint)\n\u001b[1;32m---> <a href='vscode-notebook-cell:/e%3A/Sam-test/segment-anything/notebooks/automatic_mask_generator_example.ipynb#X22sZmlsZQ%3D%3D?line=10'>11</a>\u001b[0m sam\u001b[39m.\u001b[39;49mto(device\u001b[39m=\u001b[39;49mdevice)\n\u001b[0;32m <a href='vscode-notebook-cell:/e%3A/Sam-test/segment-anything/notebooks/automatic_mask_generator_example.ipynb#X22sZmlsZQ%3D%3D?line=12'>13</a>\u001b[0m mask_generator \u001b[39m=\u001b[39m SamAutomaticMaskGenerator(sam)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\torch\\nn\\modules\\module.py:1160\u001b[0m, in \u001b[0;36mModule.to\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 1156\u001b[0m \u001b[39mreturn\u001b[39;00m t\u001b[39m.\u001b[39mto(device, dtype \u001b[39mif\u001b[39;00m t\u001b[39m.\u001b[39mis_floating_point() \u001b[39mor\u001b[39;00m t\u001b[39m.\u001b[39mis_complex() \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m,\n\u001b[0;32m 1157\u001b[0m non_blocking, memory_format\u001b[39m=\u001b[39mconvert_to_format)\n\u001b[0;32m 1158\u001b[0m \u001b[39mreturn\u001b[39;00m t\u001b[39m.\u001b[39mto(device, dtype \u001b[39mif\u001b[39;00m t\u001b[39m.\u001b[39mis_floating_point() \u001b[39mor\u001b[39;00m t\u001b[39m.\u001b[39mis_complex() \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m, non_blocking)\n\u001b[1;32m-> 1160\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_apply(convert)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\torch\\nn\\modules\\module.py:810\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 808\u001b[0m \u001b[39mif\u001b[39;00m recurse:\n\u001b[0;32m 809\u001b[0m \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mchildren():\n\u001b[1;32m--> 810\u001b[0m module\u001b[39m.\u001b[39;49m_apply(fn)\n\u001b[0;32m 812\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m 813\u001b[0m \u001b[39mif\u001b[39;00m torch\u001b[39m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m 814\u001b[0m \u001b[39m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m 815\u001b[0m \u001b[39m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 820\u001b[0m \u001b[39m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m 821\u001b[0m \u001b[39m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\torch\\nn\\modules\\module.py:810\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 808\u001b[0m \u001b[39mif\u001b[39;00m recurse:\n\u001b[0;32m 809\u001b[0m \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mchildren():\n\u001b[1;32m--> 810\u001b[0m module\u001b[39m.\u001b[39;49m_apply(fn)\n\u001b[0;32m 812\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m 813\u001b[0m \u001b[39mif\u001b[39;00m torch\u001b[39m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m 814\u001b[0m \u001b[39m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m 815\u001b[0m \u001b[39m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 820\u001b[0m \u001b[39m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m 821\u001b[0m \u001b[39m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\torch\\nn\\modules\\module.py:810\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 808\u001b[0m \u001b[39mif\u001b[39;00m recurse:\n\u001b[0;32m 809\u001b[0m \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mchildren():\n\u001b[1;32m--> 810\u001b[0m module\u001b[39m.\u001b[39;49m_apply(fn)\n\u001b[0;32m 812\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m 813\u001b[0m \u001b[39mif\u001b[39;00m torch\u001b[39m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m 814\u001b[0m \u001b[39m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m 815\u001b[0m \u001b[39m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 820\u001b[0m \u001b[39m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m 821\u001b[0m \u001b[39m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\torch\\nn\\modules\\module.py:833\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn, recurse)\u001b[0m\n\u001b[0;32m 829\u001b[0m \u001b[39m# Tensors stored in modules are graph leaves, and we don't want to\u001b[39;00m\n\u001b[0;32m 830\u001b[0m \u001b[39m# track autograd history of `param_applied`, so we have to use\u001b[39;00m\n\u001b[0;32m 831\u001b[0m \u001b[39m# `with torch.no_grad():`\u001b[39;00m\n\u001b[0;32m 832\u001b[0m \u001b[39mwith\u001b[39;00m torch\u001b[39m.\u001b[39mno_grad():\n\u001b[1;32m--> 833\u001b[0m param_applied \u001b[39m=\u001b[39m fn(param)\n\u001b[0;32m 834\u001b[0m should_use_set_data \u001b[39m=\u001b[39m compute_should_use_set_data(param, param_applied)\n\u001b[0;32m 835\u001b[0m \u001b[39mif\u001b[39;00m should_use_set_data:\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\torch\\nn\\modules\\module.py:1158\u001b[0m, in \u001b[0;36mModule.to.<locals>.convert\u001b[1;34m(t)\u001b[0m\n\u001b[0;32m 1155\u001b[0m \u001b[39mif\u001b[39;00m convert_to_format \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39mand\u001b[39;00m t\u001b[39m.\u001b[39mdim() \u001b[39min\u001b[39;00m (\u001b[39m4\u001b[39m, \u001b[39m5\u001b[39m):\n\u001b[0;32m 1156\u001b[0m \u001b[39mreturn\u001b[39;00m t\u001b[39m.\u001b[39mto(device, dtype \u001b[39mif\u001b[39;00m t\u001b[39m.\u001b[39mis_floating_point() \u001b[39mor\u001b[39;00m t\u001b[39m.\u001b[39mis_complex() \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m,\n\u001b[0;32m 1157\u001b[0m non_blocking, memory_format\u001b[39m=\u001b[39mconvert_to_format)\n\u001b[1;32m-> 1158\u001b[0m \u001b[39mreturn\u001b[39;00m t\u001b[39m.\u001b[39;49mto(device, dtype \u001b[39mif\u001b[39;49;00m t\u001b[39m.\u001b[39;49mis_floating_point() \u001b[39mor\u001b[39;49;00m t\u001b[39m.\u001b[39;49mis_complex() \u001b[39melse\u001b[39;49;00m \u001b[39mNone\u001b[39;49;00m, non_blocking)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\torch\\cuda\\__init__.py:289\u001b[0m, in \u001b[0;36m_lazy_init\u001b[1;34m()\u001b[0m\n\u001b[0;32m 284\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mRuntimeError\u001b[39;00m(\n\u001b[0;32m 285\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mCannot re-initialize CUDA in forked subprocess. To use CUDA with \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 286\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mmultiprocessing, you must use the \u001b[39m\u001b[39m'\u001b[39m\u001b[39mspawn\u001b[39m\u001b[39m'\u001b[39m\u001b[39m start method\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 287\u001b[0m )\n\u001b[0;32m 288\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mhasattr\u001b[39m(torch\u001b[39m.\u001b[39m_C, \u001b[39m\"\u001b[39m\u001b[39m_cuda_getDeviceCount\u001b[39m\u001b[39m\"\u001b[39m):\n\u001b[1;32m--> 289\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mAssertionError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mTorch not compiled with CUDA enabled\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m 290\u001b[0m \u001b[39mif\u001b[39;00m _cudart \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m 291\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mAssertionError\u001b[39;00m(\n\u001b[0;32m 292\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mlibcudart functions unavailable. It looks like you have a broken build?\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 293\u001b[0m )\n",
"\u001b[1;31mAssertionError\u001b[0m: Torch not compiled with CUDA enabled"
]
}
],
"source": [
"import sys\n",
"sys.path.append(\"..\")\n",
@@ -245,7 +264,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": null,
"id": "391771c1",
"metadata": {},
"outputs": [],
@@ -270,7 +289,7 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": null,
"id": "4fae8d66",
"metadata": {},
"outputs": [
@@ -297,7 +316,7 @@
},
{
"cell_type": "code",
"execution_count": 28,
"execution_count": null,
"id": "77ac29c5",
"metadata": {
"scrolled": false
@@ -340,7 +359,7 @@
},
{
"cell_type": "code",
"execution_count": 24,
"execution_count": null,
"id": "68364513",
"metadata": {},
"outputs": [],
@@ -358,7 +377,7 @@
},
{
"cell_type": "code",
"execution_count": 25,
"execution_count": null,
"id": "bebcdaf1",
"metadata": {},
"outputs": [],
@@ -368,7 +387,7 @@
},
{
"cell_type": "code",
"execution_count": 26,
"execution_count": null,
"id": "b8473f3c",
"metadata": {},
"outputs": [
@@ -389,7 +408,7 @@
},
{
"cell_type": "code",
"execution_count": 27,
"execution_count": null,
"id": "fb702ae3",
"metadata": {},
"outputs": [
@@ -437,7 +456,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.0"
"version": "3.10.11"
}
},
"nbformat": 4,