Update app.py

app.py

@@ -44,7 +44,7 @@ prompt_df = pd.read_csv("Stable-Diffusion-Prompts.csv")
 #DEFAULT_PROMPT = "1girl, aqua eyes, baseball cap, blonde hair, closed mouth, earrings, green background, hat, hoop earrings, jewelry, looking at viewer, shirt, short hair, simple background, solo, upper body, yellow shirt"
 DEFAULT_PROMPT = "X go to Istanbul"
 DEFAULT_ROLE = "Superman"
-DEFAULT_BOOK_COVER = "book_cover_dir/JMW_Turner_-_Nantes_from_the_Ile_Feydeau.jpg"
+DEFAULT_BOOK_COVER = "book_cover_dir/Blank.jpg"
 
 hub_module = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2')
 
@@ -422,19 +422,20 @@ def style_transfer_func(content_img, style_img, style_transfer_client = style_tr
     os.remove(style_im_name)
     return Image.open(out)
 '''
-def style_transfer_func(content_img, style_img):
+def style_transfer_func(content_img, style_img, super_resolution_type = "none"):
     assert hasattr(content_img, "save")
     assert hasattr(style_img, "save")
     content_image_input = np.asarray(content_img)
     style_image_input = np.asarray(style_img)
-    out = perform_neural_transfer(content_image_input, style_image_input, super_resolution_type = "none")
+    out = perform_neural_transfer(content_image_input, style_image_input, super_resolution_type = super_resolution_type)
     assert hasattr(out, "save")
     return out
 
 
 def gen_images_from_event_fact(current_model, event_fact = DEFAULT_PROMPT, role_name = DEFAULT_ROLE,
-    style_pic = None
+    style_pic = None, super_resolution_type = "SD(Standard Definition)"
 ):
+    assert super_resolution_type in ["SD(Standard Definition)", "HD(High Definition)"]
     event_reasoning_dict = produce_4_event(event_fact)
     caption_list ,event_reasoning_sd_list = transform_4_event_as_sd_prompts(event_fact ,
         event_reasoning_dict,
@@ -451,9 +452,14 @@ def gen_images_from_event_fact(current_model, event_fact = DEFAULT_PROMPT, role_
         print("perform styling.....")
         img_list_ = []
         for x in tqdm(img_list):
-            img_list_.append(
-                    style_transfer_func(x, style_pic)
-                )
+            if super_resolution_type == "SD(Standard Definition)":
+                img_list_.append(
+                        style_transfer_func(x, style_pic, super_resolution_type = "none")
+                    )
+            else:
+                img_list_.append(
+                        style_transfer_func(x, style_pic, super_resolution_type = "anime")
+                    )
         img_list = img_list_
     img_list = list(map(lambda t2: add_caption_on_image(t2[0], t2[1]) ,zip(*[img_list, caption_list])))
     img_mid = img_list[2]
@@ -466,7 +472,9 @@ def gen_images_from_event_fact(current_model, event_fact = DEFAULT_PROMPT, role_
 
 def image_click(images, evt: gr.SelectData,
     ):
-    img_selected = images[evt.index]["name"]
+    #print(images)
+    #print(evt.index)
+    img_selected = images[evt.index][0]["name"]
     #print(img_selected)
     return img_selected
 
@@ -475,10 +483,13 @@ def get_book_covers():
     list(pathlib.Path("book_cover_dir").rglob("*.jpg")) + \
     list(pathlib.Path("book_cover_dir").rglob("*.png")) + \
     list(pathlib.Path("book_cover_dir").rglob("*.jpeg"))
-    ).map(str).map(lambda x: np.nan if x.split("/")[-1].startswith("_") else x).dropna().values.tolist()
+    ).map(str).map(lambda x: np.nan if x.split("/")[-1].startswith("_") else x).dropna().map(
+        lambda x: (x, "".join(x.split(".")[:-1]).split("/")[-1])
+    ).values.tolist()
+    covers = sorted(covers, key = lambda t2: int(DEFAULT_BOOK_COVER in t2[0]), reverse = True)
     return covers
 
-with gr.Blocks() as demo:
+with gr.Blocks(css=".caption-label {display:none}") as demo:
     favicon = '<img src="" width="48px" style="display: inline">'
     gr.Markdown(
         f"""<h1><center>🌻{favicon} AI Diffusion</center></h1>
@@ -499,6 +510,9 @@ with gr.Blocks() as demo:
                             value = DEFAULT_BOOK_COVER,
                             interactive = True,
                             )
+            super_resolution_type = gr.Radio(choices = ["SD(Standard Definition)" ,"HD(High Definition)"],
+                        value="SD(Standard Definition)", label="Story Video Quality",
+                                                 interactive = True)
 
             with gr.Row():
                 text_prompt = gr.Textbox(label="Prompt", placeholder="a cute dog", lines=1, elem_id="prompt-text-input", value = DEFAULT_PROMPT)
@@ -515,7 +529,7 @@ with gr.Blocks() as demo:
             image_click, style_reference_input_gallery, style_reference_input_image
     )
 
-    text_button.click(gen_images_from_event_fact, inputs=[current_model, text_prompt, role_name, style_reference_input_image],
+    text_button.click(gen_images_from_event_fact, inputs=[current_model, text_prompt, role_name, style_reference_input_image, super_resolution_type],
         outputs=video_output)
 
     #select_button.click(generate_txt2img, inputs=[current_model, select_prompt, negative_prompt, image_style], outputs=image_output)