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examples/integrations/sam/meta_sam_labelbox_video.ipynb

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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Thu Jun 1 17:47:12 2023 \n",
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"+-----------------------------------------------------------------------------+\n",
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"| NVIDIA-SMI 525.85.12 Driver Version: 525.85.12 CUDA Version: 12.0 |\n",
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"|-------------------------------+----------------------+----------------------+\n",
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"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
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"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
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"| | | MIG M. |\n",
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"|===============================+======================+======================|\n",
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"| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n",
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"| N/A 75C P8 12W / 70W | 0MiB / 15360MiB | 0% Default |\n",
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"| | | N/A |\n",
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"+-------------------------------+----------------------+----------------------+\n",
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" \n",
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"+-----------------------------------------------------------------------------+\n",
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"| Processes: |\n",
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"| GPU GI CI PID Type Process name GPU Memory |\n",
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"| ID ID Usage |\n",
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"|=============================================================================|\n",
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"| No running processes found |\n",
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"+-----------------------------------------------------------------------------+\n"
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"/bin/bash: nvidia-smi: command not found\n"
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]
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}
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],
@@ -381,9 +362,9 @@
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"\u001b[?25l \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m0.0/209.1 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m209.1/209.1 kB\u001b[0m \u001b[31m17.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25l \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m0.0/209.1 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m209.1/209.1 kB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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"\u001b[2K \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m7.7/7.7 MB\u001b[0m \u001b[31m70.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u001b[0m \u001b[32m7.7/7.7 MB\u001b[0m \u001b[31m75.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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" Building wheel for backports-datetime-fromisoformat (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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" Building wheel for pygeotile (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
@@ -411,7 +392,7 @@
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"# https://docs.labelbox.com/reference/create-api-key\n",
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"# Then, fill it in here\n",
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"\n",
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"API_KEY = \"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjbDc1Znp0dmszbmljMDd6bjR1Mm1mN3ZrIiwib3JnYW5pemF0aW9uSWQiOiJjbDc1Znp0djkzbmliMDd6bmJndnYwMGw4IiwiYXBpS2V5SWQiOiJjbGg4dXFrcmIwYnVvMDd6OTFtNmE1M2NxIiwic2VjcmV0IjoiZTY0NWE1MGI5MGNjZWUwNmM2Mzc3NmQ1YTE4MmIwZWUiLCJpYXQiOjE2ODMxODgxMDMsImV4cCI6MjMxNDM0MDEwM30.6nm9lzUONVXFKBxVGJZ7a50_j4l3HSjO9wvs8MP3C6I\"\n",
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"API_KEY = \"\"\n",
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"client = lb.Client(API_KEY)"
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],
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"cell_type": "code",
@@ -725,8 +706,7 @@
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"# Project defaults to batch mode with benchmark quality settings if this argument is not provided\n",
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"# Queue mode will be deprecated once dataset mode is deprecated\n",
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"project = client.create_project(name=\"yolo-sam-video-masks-project\",\n",
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" media_type=lb.MediaType.Video,\n",
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" queue_mode=lb.QueueMode.Batch)\n",
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" media_type=lb.MediaType.Video)\n",
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"\n",
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"# Or get an existing project by ID (uncomment the below)\n",
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"\n",
@@ -744,14 +724,17 @@
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"source": [
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"# Create a new batch of data for the project you specified above\n",
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"\n",
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"data_row_ids = client.get_data_row_ids_for_global_keys([global_key])['results']\n",
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"# Uncomment if you are using `data_rows` parameter below\n",
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"# data_row_ids = client.get_data_row_ids_for_global_keys([global_key])['results']\n",
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"\n",
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"batch = project.create_batch(\n",
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" \"yolo-sam-video-masks-project\", # each batch in a project must have a unique name\n",
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" data_rows=data_row_ids,\n",
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" \n",
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" # you can also specify global_keys instead of data_rows\n",
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" #global_keys=[global_key], # paginated collection of data row objects, list of data row ids or global keys\n",
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" global_keys=[global_key],\n",
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"\n",
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" # you can also specify data_rows instead of global_keys\n",
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" #data_rows=data_row_ids,\n",
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" \n",
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" priority=1 # priority between 1(highest) - 5(lowest)\n",
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")\n",

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