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import gradio as gr
from PIL import Image
import tempfile
def predict_depth(model, image):
depth = model.infer_pil(image)
return depth
def create_demo():
with gr.Row():
with gr.Column(scale=1):
model_type = gr.Dropdown(["Prismer-Base", "Prismer-Large"], label="Model Size", value="Prismer-Base")
rgb = gr.Image(label="Input Image", type='pil')
submit = gr.Button("Submit")
with gr.Column(scale=2):
pred = gr.Textbox(label="Model Prediction")
with gr.Row():
depth = gr.Image(label="Depth")
edge = gr.Image(label="Edge")
normals = gr.Image(label="Normals")
with gr.Row():
seg = gr.Image(label="Segmentation")
obj_det = gr.Image(label="Object Detection")
ocr_det = gr.Image(label="OCR Detection")
def on_submit(im, model_type):
return pred, depth, edge, normals, seg, obj_det, ocr_det
submit.click(on_submit, inputs=[rgb, model_type], outputs=[pred, depth, edge, normals, seg, obj_det, ocr_det])
examples = gr.Examples(examples=["examples/1.png"], inputs=[rgb])
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