Mention models

gradio_demo.py

@@ -117,7 +117,6 @@ def llave_process(input_image, temperature, top_p, qs=None):
     print('<<== llave_process')
     return captions[0]
 
-@spaces.GPU(duration=540)
 def stage2_process(
     noisy_image,
     denoise_image,
@@ -146,6 +145,66 @@ def stage2_process(
     spt_linear_s_stage2,
     model_select,
     output_format
+):
+    restore(
+        noisy_image,
+        denoise_image,
+        prompt,
+        a_prompt,
+        n_prompt,
+        num_samples,
+        min_size,
+        downscale,
+        upscale,
+        edm_steps,
+        s_stage1,
+        s_stage2,
+        s_cfg,
+        randomize_seed,
+        seed,
+        s_churn,
+        s_noise,
+        color_fix_type,
+        diff_dtype,
+        ae_dtype,
+        gamma_correction,
+        linear_CFG,
+        linear_s_stage2,
+        spt_linear_CFG,
+        spt_linear_s_stage2,
+        model_select,
+        output_format
+    )
+
+@spaces.GPU(duration=540)
+def restore(
+    noisy_image,
+    denoise_image,
+    prompt,
+    a_prompt,
+    n_prompt,
+    num_samples,
+    min_size,
+    downscale,
+    upscale,
+    edm_steps,
+    s_stage1,
+    s_stage2,
+    s_cfg,
+    randomize_seed,
+    seed,
+    s_churn,
+    s_noise,
+    color_fix_type,
+    diff_dtype,
+    ae_dtype,
+    gamma_correction,
+    linear_CFG,
+    linear_s_stage2,
+    spt_linear_CFG,
+    spt_linear_s_stage2,
+    model_select,
+    output_format
 ):
     start = time.time()
     print('stage2_process ==>>')
@@ -364,7 +423,7 @@ with gr.Blocks(title="SUPIR") as interface:
         downscale = gr.Radio([["/1", 1], ["/2", 2], ["/3", 3], ["/4", 4], ["/5", 5], ["/6", 6], ["/7", 7], ["/8", 8]], label="Pre-downscale factor", info="Reducing blurred image reduce the process time", value=1, interactive=True)
         with gr.Row():
             with gr.Column():
-                model_select = gr.Radio([["💃 Quality", "v0-Q"], ["🎯 Fidelity", "v0-F"]], label="Model Selection", info="Pretrained model", value="v0-Q",
+                model_select = gr.Radio([["💃 Quality (v0-Q)", "v0-Q"], ["🎯 Fidelity (v0-F)", "v0-F"]], label="Model Selection", info="Pretrained model", value="v0-Q",
                                         interactive=True)
             with gr.Column():
                 color_fix_type = gr.Radio(["None", "AdaIn", "Wavelet"], label="Color-Fix Type", info="AdaIn=Improve following a style, Wavelet=For JPEG artifacts", value="Wavelet",