app.py

import os

import gradio as gr

from inference import inference

input_video = gr.Video(mirror_webcam=False)

dd_model = gr.Dropdown(choices=["YoloV7"], value="YoloV7", label="Model")

cb_motion_estimation = gr.Checkbox(value=True, label="Track camera movement")

cb_path_draw = gr.Checkbox(value=True, label="Draw objects paths")

dd_track_points = gr.Dropdown(
    choices=["Boxes", "Centroid"], value="Boxes", label="Detections style"
)

slide_threshold = gr.Slider(minimum=0, maximum=1, value=0.25, label="Model confidence threshold")

# examples_folder = "examples"
# examples_list = []

# if os.path.isdir(examples_folder):
#     for file in os.listdir(examples_folder):
#         path = examples_folder + "/" + file
#         examples_list.append([path])

output_component = "playablevideo"

iface = gr.Interface(
    fn=inference,
    inputs=[
        input_video,
        dd_model,
        cb_motion_estimation,
        cb_path_draw,
        dd_track_points,
        slide_threshold,
    ],
    outputs=output_component,
)

iface.launch()