refactor: simplify ELA function name and clean up unused augmentations in Gradio interface

app_mcp.py

@@ -15,7 +15,7 @@ import logging
 from utils.utils import softmax, augment_image, convert_pil_to_bytes
 from utils.gradient import gradient_processing
 from utils.minmax import minmax_process
-from utils.ela import genELA as ELA
+from utils.ela import ELA
 from utils.wavelet import wavelet_blocking_noise_estimation
 from utils.bitplane import bit_plane_extractor
 from utils.hf_logger import log_inference_data
@@ -524,12 +524,7 @@ with gr.Blocks(css="#post-gallery { overflow: hidden !important;} .grid-wrap{ ov
                 consensus_md = gr.Markdown(label="Consensus", value="")
 
                 outputs = [image_output, forensics_gallery, results_table, debug_json, consensus_md]
-        
-        # Show/hide rotate slider based on selected augmentation method
-        augment_checkboxgroup.change(lambda methods: gr.update(visible="rotate" in methods), inputs=[augment_checkboxgroup], outputs=[rotate_slider])
-        augment_checkboxgroup.change(lambda methods: gr.update(visible="add_noise" in methods), inputs=[augment_checkboxgroup], outputs=[noise_slider])
-        augment_checkboxgroup.change(lambda methods: gr.update(visible="sharpen" in methods), inputs=[augment_checkboxgroup], outputs=[sharpen_slider])
-        
+
         predict_button.click(
             fn=predict_with_ensemble, 
             inputs=inputs, 

utils/ela.py

@@ -24,7 +24,7 @@ def elapsed_time(start):
     """Calculate elapsed time since start."""
     return f"{time() - start:.3f}s"
 
-def genELA(img, quality=75, scale=50, contrast=20, linear=False, grayscale=False):
+def ELA(img, quality=75, scale=50, contrast=20, linear=False, grayscale=False):
     """
     Perform Error Level Analysis on an image.