API
If you're looking for an API, you can choose from your desired programming language.
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import requests
import base64
# Use this function to convert an image file from the filesystem to base64
def image_file_to_base64(image_path):
with open(image_path, 'rb') as f:
image_data = f.read()
return base64.b64encode(image_data).decode('utf-8')
# Use this function to fetch an image from a URL and convert it to base64
def image_url_to_base64(image_url):
response = requests.get(image_url)
image_data = response.content
return base64.b64encode(image_data).decode('utf-8')
api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/automatic-mask-generator"
# Request payload
data = {
"prompt": "Sofa",
"image": image_url_to_base64("https://segmind-sd-models.s3.amazonaws.com/display_images/automask-ip.jpg"), # Or use image_file_to_base64("IMAGE_PATH")
"threshold": 0.2,
"invert_mask": False,
"return_mask": True,
"grow_mask": 10,
"seed": 468685,
"base64": False
}
headers = {'x-api-key': api_key}
response = requests.post(url, json=data, headers=headers)
print(response.content) # The response is the generated imageAttributes
Prompt to render
Upload your input image
Detection threshold
min : 0,
max : 1
Refers to inverting the mask.
Check this to obtain the mask as the output.
Selectively expand image regions
min : 0,
max : 100
Seed for image generation.
min : -1,
max : 999999999999999
Base64 encoding of the output image.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
PixelFlow allows you to use all these features
Unlock the full potential of generative AI with Segmind. Create stunning visuals and innovative designs with total creative control. Take advantage of powerful development tools to automate processes and models, elevating your creative workflow.
Segmented Creation Workflow
Gain greater control by dividing the creative process into distinct steps, refining each phase.
Customized Output
Customize at various stages, from initial generation to final adjustments, ensuring tailored creative outputs.
Layering Different Models
Integrate and utilize multiple models simultaneously, producing complex and polished creative results.
Workflow APIs
Deploy Pixelflows as APIs quickly, without server setup, ensuring scalability and efficiency.
Automatic Mask Generator
Automatic Mask Generator is a powerful tool that automates the creation of precise masks for inpainting. This innovative solution streamlines your workflow by combining the strengths of two cutting-edge AI models: Grounding DINO and Segment Anything Model (SAM).
Targeted Object Detection with Grounding DINO: The process starts with Grounding DINO, acting as a highly accurate object detector. Imagine feeding an image along with a specific object category (e.g., "cat" or "building") to Grounding DINO. It meticulously analyzes the image and pinpoints the location of the desired object with exceptional precision.
Seamless Segmentation with SAM: Once Grounding DINO identifies the object of interest, SAM takes center stage. SAM, a segmentation powerhouse, meticulously analyzes the image, focusing specifically on the object identified by Grounding DINO. This targeted segmentation separates the object from the rest of the image, creating a clear distinction.
Mask Generation for Precise Inpainting: With the object neatly segmented, Automatic Mask Generator creates a high-quality mask. This mask acts as a blueprint for Stable Diffusion inpainting. Black pixels within the mask represent areas to be preserved (the object itself), while white pixels indicate areas to be filled by the inpainting process. This precise definition ensures Stable Diffusion focuses on the desired inpainting area, leading to more accurate and realistic results.
Benefits of Automatic Mask Generation
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Enhanced Efficiency: Automating mask creation eliminates time-consuming manual processes, allowing you to focus on creative aspects of inpainting.
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Improved Accuracy: The combined power of Grounding DINO and SAM ensures precise object detection and segmentation, leading to more accurate masks and superior inpainting outcomes.
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Simplified Workflow: Automatic Mask Generator streamlines your workflow by handling mask creation, enabling you to seamlessly transition to the inpainting stage.
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Greater Control: Precise masks provide greater control over the inpainting process, allowing you to refine the results to your specific vision.
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