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import gradio as gr
import os
from modules.sam_inference import SamInference
from modules.model_downloader import DEFAULT_MODEL_TYPE
from modules.paths import OUTPUT_DIR
from modules.utils import open_folder
class App:
def __init__(self,
args = None):
self.app = gr.Blocks()
self.args = args
self.sam_inf = SamInference()
def launch(self):
with self.app:
with gr.Row():
with gr.Column(scale=5):
with gr.Tabs() as tabs_sources:
with gr.TabItem("Image Input"):
img_input = gr.Image(label="Input image here")
with gr.TabItem("Video Input"):
vid_input = gr.Image(label="Input video here")
with gr.Column(scale=5):
dd_models = gr.Dropdown(label="Model", value=DEFAULT_MODEL_TYPE, choices=self.sam_inf.available_models)
with gr.Accordion("Mask Parameters", open=False) as mask_hparams:
nb_points_per_side = gr.Number(label="points_per_side ", value=64, interactive=True)
nb_points_per_batch = gr.Number(label="points_per_batch ", value=128, interactive=True)
sld_pred_iou_thresh = gr.Slider(label="pred_iou_thresh ", value=0.7, minimum=0, maximum=1,
interactive=True)
sld_stability_score_thresh = gr.Slider(label="stability_score_thresh ", value=0.92, minimum=0,
maximum=1, interactive=True)
sld_stability_score_offset = gr.Slider(label="stability_score_offset ", value=0.7, minimum=0,
maximum=1)
nb_crop_n_layers = gr.Number(label="crop_n_layers ", value=1)
sld_box_nms_thresh = gr.Slider(label="box_nms_thresh ", value=0.7, minimum=0,
maximum=1)
nb_crop_n_points_downscale_factor = gr.Number(label="crop_n_points_downscale_factor ", value=2)
nb_min_mask_region_area = gr.Number(label="min_mask_region_area ", value=25)
cb_use_m2m = gr.Checkbox(label="use_m2m ", value=True)
with gr.Row():
btn_generate = gr.Button("GENERATE", variant="primary")
with gr.Row():
gallery_output = gr.Gallery(label="Output images will be shown here")
with gr.Column():
output_file = gr.File(label="Generated psd file", scale=9)
btn_open_folder = gr.Button("📁\nOpen PSD folder", scale=1)
sources = [img_input or vid_input]
model_params = [dd_models]
auto_mask_hparams = [nb_points_per_side, nb_points_per_batch, sld_pred_iou_thresh,
sld_stability_score_thresh, sld_stability_score_offset, nb_crop_n_layers,
sld_box_nms_thresh, nb_crop_n_points_downscale_factor, nb_min_mask_region_area,
cb_use_m2m]
btn_generate.click(fn=self.sam_inf.generate_mask_app,
inputs=sources + model_params + auto_mask_hparams, outputs=[gallery_output, output_file])
btn_open_folder.click(fn=lambda: open_folder(os.path.join(OUTPUT_DIR)),
inputs=None, outputs=None)
self.app.queue().launch(inbrowser=True)
if __name__ == "__main__":
app = App()
app.launch()
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