Update app.py

app.py

@@ -1,33 +1,20 @@
 #!/usr/bin/env python3
 import gradio as gr
 from clip_interrogator import Config, Interrogator
-from share_btn import community_icon_html, loading_icon_html, share_js
 
-MODELS = ['ViT-L (best for Stable Diffusion 1.*)', 'ViT-H (best for Stable Diffusion 2.*)']
+# MODELS = ['ViT-L (best for Stable Diffusion 1.*)', 'ViT-H (best for Stable Diffusion 2.*)']
+# MODELS = ['ViT-L (best for Stable Diffusion 1.*)',]
 
 # load BLIP and ViT-L https://huggingface.co/openai/clip-vit-large-patch14
 config = Config(clip_model_name="ViT-L-14/openai")
-ci_vitl = Interrogator(config)
-ci_vitl.clip_model = ci_vitl.clip_model.to("cpu")
-
-# load ViT-H https://huggingface.co/laion/CLIP-ViT-H-14-laion2B-s32B-b79K
-config.blip_model = ci_vitl.blip_model
-config.clip_model_name = "ViT-H-14/laion2b_s32b_b79k"
-ci_vith = Interrogator(config)
-ci_vith.clip_model = ci_vith.clip_model.to("cpu")
-
-
-def image_analysis(image, clip_model_name):
-    # move selected model to GPU and other model to CPU
-    if clip_model_name == MODELS[0]:
-        ci_vith.clip_model = ci_vith.clip_model.to("cpu")
-        ci_vitl.clip_model = ci_vitl.clip_model.to(ci_vitl.device)
-        ci = ci_vitl
-    else:
-        ci_vitl.clip_model = ci_vitl.clip_model.to("cpu")
-        ci_vith.clip_model = ci_vith.clip_model.to(ci_vith.device)
-        ci = ci_vith
 
+ci = Interrogator(config)
+ci.clip_model = ci_vitl.clip_model.to("cpu")
+ci.config.blip_num_beams = 64
+ci.config.chunk_size = 2048
+ci.config.flavor_intermediate_count = 2048 #  1024
+
+def image_analysis(image):
     image = image.convert('RGB')
     image_features = ci.image_to_features(image)
 
@@ -47,20 +34,6 @@ def image_analysis(image, clip_model_name):
 
 
 def image_to_prompt(image, clip_model_name, mode):
-    # move selected model to GPU and other model to CPU
-    if clip_model_name == MODELS[0]:
-        ci_vith.clip_model = ci_vith.clip_model.to("cpu")
-        ci_vitl.clip_model = ci_vitl.clip_model.to(ci_vitl.device)
-        ci = ci_vitl
-    else:
-        ci_vitl.clip_model = ci_vitl.clip_model.to("cpu")
-        ci_vith.clip_model = ci_vith.clip_model.to(ci_vith.device)
-        ci = ci_vith
-
-    ci.config.blip_num_beams = 64
-    ci.config.chunk_size = 2048
-    ci.config.flavor_intermediate_count = 2048 if clip_model_name == MODELS[0] else 1024
-
     image = image.convert('RGB')
     if mode == 'best':
         prompt = ci.interrogate(image)
@@ -71,7 +44,7 @@ def image_to_prompt(image, clip_model_name, mode):
     elif mode == 'negative':
         prompt = ci.interrogate_negative(image)
 
-    return prompt, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
+    return prompt
 
 
 TITLE = """
@@ -163,7 +136,7 @@ def analyze_tab():
     ex = gr.Examples(
         examples=examples, 
         fn=image_analysis, 
-        inputs=[input_image, input_model], 
+        inputs=[input_image], 
         outputs=[medium, artist, movement, trending, flavor], 
         cache_examples=True, 
         run_on_click=True
@@ -179,22 +152,16 @@ with gr.Blocks(css=CSS) as block:
             with gr.Row():
                 input_image = gr.Image(type='pil', elem_id="input-img")
                 with gr.Column():
-                    input_model = gr.Dropdown(MODELS, value=MODELS[0], label='CLIP Model')
                     input_mode = gr.Radio(['best', 'fast', 'classic', 'negative'], value='best', label='Mode')
             submit_btn = gr.Button("Submit", api_name="image-to-prompt")
             output_text = gr.Textbox(label="Output", elem_id="output-txt")
 
-            with gr.Group(elem_id="share-btn-container"):
-                community_icon = gr.HTML(community_icon_html, visible=False)
-                loading_icon = gr.HTML(loading_icon_html, visible=False)
-                share_button = gr.Button("Share to community", elem_id="share-btn", visible=False)
-
             examples=[['example01.jpg', MODELS[0], 'best'], ['example02.jpg', MODELS[0], 'best']]
             ex = gr.Examples(
                 examples=examples, 
                 fn=image_to_prompt, 
                 inputs=[input_image, input_model, input_mode], 
-                outputs=[output_text, share_button, community_icon, loading_icon], 
+                outputs=[output_text], 
                 cache_examples=True, 
                 run_on_click=True
             )
@@ -208,8 +175,8 @@ with gr.Blocks(css=CSS) as block:
     submit_btn.click(
         fn=image_to_prompt, 
         inputs=[input_image, input_model, input_mode], 
-        outputs=[output_text, share_button, community_icon, loading_icon]
+        outputs=[output_text]
     )
     share_button.click(None, [], [], _js=share_js)
 
-block.queue(max_size=64).launch(show_api=False)
+block.queue(max_size=64).launch(show_api=False)