File size: 1,685 Bytes
e52a7fb 7137256 e52a7fb 7137256 e52a7fb 7137256 8d70ec1 7137256 8d70ec1 7137256 e52a7fb 7137256 e52a7fb 7137256 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | import gradio as gr
import app_backend
gr.set_static_paths(['.'])
def detect_crashes(name, sim_files, real_files, frame_out, text_output, file_out, video_out):
for outputs in app_backend.backend(name, sim_files, real_files, frame_out, text_output, file_out, video_out):
yield outputs
with gr.Blocks(title="Drone Crash Detection") as demo:
text_output = gr.Textbox(interactive=False)
frame_output = gr.Image(interactive=False)
video_output = gr.Gallery(interactive=False)
file_output = gr.File(interactive=False)
label = gr.Label("Drone Crash Classification Using Yolov8.", scale=0, show_label=False)
student_name_tb = gr.Textbox(
lines=1,
placeholder="Enter student's name. Ex: 'First Last'",
visible=True,
show_label=True,
label="Student's Name"
)
simulation_videos_upload = gr.File(
label="Upload Simulation Drone Videos",
type="filepath", # Changed 'file' to 'filepath'
file_count="multiple"
)
real_videos_upload = gr.File(
label="Upload Real Drone Videos",
type="filepath", # Changed 'file' to 'filepath'
file_count="multiple"
)
with gr.Row():
btn_prompt = gr.Button("Detect Crashes")
btn_prompt.click(
fn=detect_crashes,
inputs=[
student_name_tb,
simulation_videos_upload,
real_videos_upload,
frame_output,
text_output,
file_output,
video_output
],
outputs=[frame_output, text_output, file_output, video_output]
)
demo.launch()
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