Spaces:
Sleeping
Sleeping
| 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") | |
| ques = gr.Textbox(label="Question", placeholder="What's the number of this player?") | |
| rgb = gr.Image(label="Input Image", type='pil', elem_id='img-display-input').style(height="auto") | |
| submit = gr.Button("Submit") | |
| with gr.Column(scale=2): | |
| pred = gr.Textbox(label="Model Prediction") | |
| with gr.Row(): | |
| depth = gr.Image(label="Depth", elem_id='img-display-output') | |
| edge = gr.Image(label="Edge", elem_id='img-display-output') | |
| normals = gr.Image(label="Normals", elem_id='img-display-output') | |
| with gr.Row(): | |
| seg = gr.Image(label="Segmentation", elem_id='img-display-output') | |
| obj_det = gr.Image(label="Object Detection", elem_id='img-display-output') | |
| ocr_det = gr.Image(label="OCR Detection", elem_id='img-display-output') | |
| def on_submit(im, q, model_type): | |
| return pred, depth, edge, normals, seg, obj_det, ocr_det | |
| submit.click(on_submit, inputs=[rgb, ques, model_type], outputs=[pred, depth, edge, normals, seg, obj_det, ocr_det]) | |
| examples = gr.Examples(examples=["examples/1.png"], inputs=[rgb]) | |