Stabilty AI/Stabilty_AI_Generate_Image_from_text.ipynb

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   "source": [
    "# Stabilty AI - Generate Image from text\n",
    "<a href=\"https://bit.ly/3JyWIk6\">Give Feedback</a> | <a href=\"https://github.com/jupyter-naas/awesome-notebooks/issues/new?assignees=&labels=bug&template=bug_report.md&title=Stabilty+AI+-+Generate+Image+from+text:+Error+short+description\">Bug report</a>"
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   "source": [
    "**Tags:** #stabilityai #png #prompt #generate #file #python"
   ]
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   "source": [
    "**Author:** [Florent Ravenel](https://www.linkedin.com/in/florent-ravenel/)"
   ]
  },
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   "source": [
    "**Last update:** 2023-04-12 (Created: 2023-02-27)"
   ]
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   "source": [
    "**Description:** This notebook will demonstrate how to execute a basic image generation call via Stability AI API."
   ]
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   "source": [
    "**References:**\n",
    "- [Stability Sign up](https://beta.dreamstudio.ai/membership)\n",
    "- [Stability Documentation](https://platform.stability.ai/)\n",
    "- [Text-to-Image](https://platform.stability.ai/docs/features/text-to-image/python)"
   ]
  },
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   "source": [
    "## Input"
   ]
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   "source": [
    "### Import libraries"
   ]
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   "source": [
    "import os\n",
    "import io\n",
    "import warnings\n",
    "from PIL import Image\n",
    "try:\n",
    "    from stability_sdk import client\n",
    "except:\n",
    "    !pip install stability-sdk --user\n",
    "    from stability_sdk import client\n",
    "import stability_sdk.interfaces.gooseai.generation.generation_pb2 as generation\n",
    "import naas"
   ]
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   "source": [
    "### Setup Variables\n",
    "- `api_key`: [Stability API Key](https://beta.dreamstudio.ai/membership?tab=apiKeys)\n",
    "- `prompt`: Sentences giving information about the image to be generated"
   ]
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   "source": [
    "# Inputs\n",
    "api_key = naas.secret.get('STABILITY_KEY') or 'sk-M5xMxxxx9N9xxxxxxddLe' # Get your API Key once you have created an account: https://beta.dreamstudio.ai/membership?tab=apiKeys\n",
    "prompt = \"expansive landscape rolling greens with blue daisies and weeping willow trees under a blue alien sky, artstation, masterful, ghibli\""
   ]
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   "source": [
    "## Model"
   ]
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   "source": [
    "### Setup environment variables and API Key"
   ]
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   "source": [
    "# Our Host URL should not be prepended with \"https\" nor should it have a trailing slash.\n",
    "os.environ['STABILITY_HOST'] = 'grpc.stability.ai:443'\n",
    "os.environ['STABILITY_KEY'] = api_key"
   ]
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   "source": [
    "### Connect to client"
   ]
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    "# Set up our connection to the API.\n",
    "stability_api = client.StabilityInference(\n",
    "    key=os.environ['STABILITY_KEY'], # API Key reference.\n",
    "    verbose=True, # Print debug messages.\n",
    "    engine=\"stable-diffusion-v1-5\", # Set the engine to use for generation.\n",
    "    # Available engines: stable-diffusion-v1 stable-diffusion-v1-5 stable-diffusion-512-v2-0 stable-diffusion-768-v2-0\n",
    "    # stable-diffusion-512-v2-1 stable-diffusion-768-v2-1 stable-inpainting-v1-0 stable-inpainting-512-v2-0\n",
    ")"
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   "source": [
    "### Requests Stability API"
   ]
  },
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    "answers = stability_api.generate(\n",
    "    prompt=prompt,\n",
    "    seed=992446758, # If a seed is provided, the resulting generated image will be deterministic.\n",
    "                    # What this means is that as long as all generation parameters remain the same, you can always recall the same image simply by generating it again.\n",
    "                    # Note: This isn't quite the case for Clip Guided generations, which we'll tackle in a future example notebook.\n",
    "    steps=30, # Amount of inference steps performed on image generation. Defaults to 30.\n",
    "    cfg_scale=8.0, # Influences how strongly your generation is guided to match your prompt.\n",
    "                   # Setting this value higher increases the strength in which it tries to match your prompt.\n",
    "                   # Defaults to 7.0 if not specified.\n",
    "    width=512, # Generation width, defaults to 512 if not included.\n",
    "    height=512, # Generation height, defaults to 512 if not included.\n",
    "    samples=1, # Number of images to generate, defaults to 1 if not included.\n",
    "    sampler=generation.SAMPLER_K_DPMPP_2M # Choose which sampler we want to denoise our generation with.\n",
    "                                                 # Defaults to k_dpmpp_2m if not specified. Clip Guidance only supports ancestral samplers.\n",
    "                                                 # (Available Samplers: ddim, plms, k_euler, k_euler_ancestral, k_heun, k_dpm_2, k_dpm_2_ancestral, k_dpmpp_2s_ancestral, k_lms, k_dpmpp_2m)\n",
    ")"
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   "source": [
    "## Output"
   ]
  },
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   "source": [
    "### Save and Display image\n",
    "Note: This is not representative of all of the parameters available for image generation.\n",
    "Please refer to our protobuf reference for a complete list of all parameters available for image generation."
   ]
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    "# Set up our warning to print to the console if the adult content classifier is tripped.\n",
    "# If adult content classifier is not tripped, save generated images.\n",
    "for resp in answers:\n",
    "    for artifact in resp.artifacts:\n",
    "        if artifact.finish_reason == generation.FILTER:\n",
    "            warnings.warn(\n",
    "                \"Your request activated the API's safety filters and could not be processed.\"\n",
    "                \"Please modify the prompt and try again.\")\n",
    "        if artifact.type == generation.ARTIFACT_IMAGE:\n",
    "            img = Image.open(io.BytesIO(artifact.binary))\n",
    "            img.save(str(artifact.seed)+ \".png\") # Save our generated images with their seed number as the filename.\n",
    "\n",
    "img"
   ]
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    " "
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