File size: 1,765 Bytes
82654de 45f24a2 82654de 3a53eae 82654de 45f24a2 3a53eae 45f24a2 3a53eae 45f24a2 82654de 3a53eae 82654de 3a53eae b3673c2 82654de 3a53eae 82654de 45f24a2 82654de 3a53eae 82654de 1871c9c 82654de 3a53eae 82654de 3a53eae 45f24a2 82654de 45f24a2 82654de |
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 53 54 55 |
import os
import sys
from pathlib import Path
import gradio as gr
from utils.data_processing import detect_nsfw
# YOLO-related module path setup
FILE = Path(__file__).resolve()
ROOT = FILE.parents[0]
if str(ROOT) not in sys.path:
sys.path.append(str(ROOT))
ROOT = Path(os.path.relpath(ROOT, Path.cwd()))
# Define the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# NSFW Content Detection - Detailed Analysis")
# Advanced parameters for Detailed Analysis
with gr.Row():
conf_threshold = gr.Slider(0, 1, value=0.2, label="Confidence Threshold")
iou_threshold = gr.Slider(0, 1, value=0.45, label="Overlap Threshold")
label_mode = gr.Dropdown(
["Draw box", "Draw Label", "Draw Confidence", "Censor Predictions"],
label="Label Display Mode",
value="Draw box",
)
# Input and output components
with gr.Row():
input_image = gr.Image(type="numpy", label="Upload an image or enter a URL")
output_text = gr.Textbox(label="Detection Result")
with gr.Row():
output_image = gr.Image(type="numpy", label="Processed Image (for detailed analysis)")
# Detection button
detect_button = gr.Button("Detect")
# Connect detection button to the detect_nsfw function
def safe_detect_nsfw(image, conf, iou, label):
try:
return detect_nsfw(image, conf, iou, label)
except Exception as e:
return f"Error during detection: {e}", None
detect_button.click(
safe_detect_nsfw,
inputs=[input_image, conf_threshold, iou_threshold, label_mode],
outputs=[output_text, output_image],
)
# Launch the Gradio app
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0")
|