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Update app.py
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app.py
CHANGED
@@ -6,7 +6,7 @@ from sentence_transformers import SentenceTransformer
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import transformers.models.clip.image_processing_clip
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import torch
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import gradio as gr
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from deep_translator import GoogleTranslator
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import shutil
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from PIL import Image
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import os
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@@ -15,7 +15,6 @@ with open('pinecone_text.py' ,'w') as fb:
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fb.write(requests.get('https://storage.googleapis.com/gareth-pinecone-datasets/pinecone_text.py').text)
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import pinecone_text
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# init connection to pinecone
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pinecone.init(
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api_key="0898750a-ee05-44f1-ac8a-98c5fef92f4a", # app.pinecone.io
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@@ -58,7 +57,6 @@ model = SentenceTransformer(
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device=device
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)
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def hybrid_scale(dense, sparse, alpha: float):
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if alpha < 0 or alpha > 1:
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raise ValueError("Alpha must be between 0 and 1")
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@@ -101,7 +99,7 @@ def img_to_file_list(imgs):
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# Check whether the specified path exists or not
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isExist = os.path.exists('.'+'/'+path)
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if not isExist:
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print("Directory does not exists")
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# Create a new directory because it does not exist
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@@ -110,7 +108,7 @@ def img_to_file_list(imgs):
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# Check whether the specified path exists or not
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isExist = os.path.exists(sub_path)
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if isExist:
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shutil.rmtree(sub_path)
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@@ -118,7 +116,7 @@ def img_to_file_list(imgs):
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img_files = {'search'+str(counter["dir_num"]):[]}
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i = 0
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for img in imgs:
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img.save(sub_path+"/img_" + str(i) + ".png","PNG")
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img_files['search'+str(counter["dir_num"])].append(sub_path + '/' + 'img_'+ str(i) + ".png")
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@@ -128,116 +126,55 @@ def img_to_file_list(imgs):
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return img_files['search'+str(counter["dir_num"]-1)]
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def
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raise ValueError("Alpha must be between 0 and 1")
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# scale sparse and dense vectors to create hybrid search vecs
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hsparse = {
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'indices': sparse['indices'],
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'values': [v * (1 - alpha) for v in sparse['values']]
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}
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hdense = [v * alpha for v in dense]
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return hdense, hsparse
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def text_to_image(query, alpha, k_results):
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sparse = bm25.transform_query(query)
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dense = model.encode(query).tolist()
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# scale sparse and dense vectors
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hdense, hsparse = hybrid_scale(dense, sparse, alpha=alpha)
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# search
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result = index.query(
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top_k=k_results,
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vector=hdense,
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sparse_vector=hsparse,
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include_metadata=True
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)
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# used returned product ids to get images
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imgs = [images[int(r["id"])] for r in result["matches"]]
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description = []
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for x in result["matches"]:
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description.append( x["metadata"]['productDisplayName'] )
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return imgs, description
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def img_to_file_list(imgs):
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path = "searches"
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sub_path = './' + path + '/' + 'search' + '_' + str(counter["dir_num"])
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# Check whether the specified path exists or not
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isExist = os.path.exists('.'+'/'+path)
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if not isExist:
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print("Directory does not exists")
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# Create a new directory because it does not exist
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os.makedirs('.'+'/'+path, exist_ok = True)
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print("The new directory is created!")
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# Check whether the specified path exists or not
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isExist = os.path.exists(sub_path)
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if isExist:
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shutil.rmtree(sub_path)
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os.makedirs(sub_path, exist_ok = True)
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img_files = {'search'+str(counter["dir_num"]):[]}
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i = 0
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for img in imgs:
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img.save(sub_path+"/img_" + str(i) + ".png","PNG")
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img_files['search'+str(counter["dir_num"])].append(sub_path + '/' + 'img_'+ str(i) + ".png")
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i+=1
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counter["dir_num"]+=1
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return img_files['search'+str(counter["dir_num"]-1)]
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counter = {"dir_num": 1}
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img_files = {'x':[]}
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def fake_gan(text, alpha):
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text_eng=GoogleTranslator(source='iw', target='en').translate(text)
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imgs, descr = text_to_image(text_eng, alpha, 3)
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img_files = img_to_file_list(imgs)
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return img_files
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def fake_text(text, alpha):
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en_text = GoogleTranslator(source='iw', target='en').translate(text)
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img , descr = text_to_image(en_text, alpha,
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return descr
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Row():
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btn = gr.Button("Generate image")
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with gr.Row():
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gallery = gr.Gallery(
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label="Generated images", show_label=False, elem_id="gallery"
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).style(columns=[8], rows=[2], object_fit='scale-down', height='auto')
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with gr.Row():
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selected = gr.Textbox(label="Product description: ", interactive=False, value = "-----> Description <-------",placeholder="Selected")
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btn.click(fake_gan, inputs=[text, alpha], outputs=gallery)
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def get_select_index(evt: gr.SelectData,text,alpha):
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eng_text = fake_text(text, alpha)[evt.index]
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#heb_text = GoogleTranslator(source='en', target='iw').translate(eng_text)
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return eng_text
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gallery.select( fn=get_select_index, inputs=[text,alpha], outputs=selected )
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demo.launch(
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import transformers.models.clip.image_processing_clip
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import torch
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import gradio as gr
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from deep_translator import GoogleTranslator, single_detection
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import shutil
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from PIL import Image
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import os
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fb.write(requests.get('https://storage.googleapis.com/gareth-pinecone-datasets/pinecone_text.py').text)
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import pinecone_text
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# init connection to pinecone
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pinecone.init(
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api_key="0898750a-ee05-44f1-ac8a-98c5fef92f4a", # app.pinecone.io
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device=device
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)
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def hybrid_scale(dense, sparse, alpha: float):
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if alpha < 0 or alpha > 1:
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raise ValueError("Alpha must be between 0 and 1")
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# Check whether the specified path exists or not
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isExist = os.path.exists('.'+'/'+path)
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if not isExist:
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print("Directory does not exists")
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# Create a new directory because it does not exist
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# Check whether the specified path exists or not
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isExist = os.path.exists(sub_path)
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if isExist:
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shutil.rmtree(sub_path)
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img_files = {'search'+str(counter["dir_num"]):[]}
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i = 0
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for img in imgs:
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img.save(sub_path+"/img_" + str(i) + ".png","PNG")
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img_files['search'+str(counter["dir_num"])].append(sub_path + '/' + 'img_'+ str(i) + ".png")
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return img_files['search'+str(counter["dir_num"]-1)]
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counter = {"dir_num": 1}
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img_files = {'x':[]}
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K = 5
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def fake_gan(text, alpha):
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detected_language = single_detection(text, api_key='d259a6dab3bb73b1d1c2bcc6fb62b9f4')
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if detected_language == 'iw':
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text_eng=GoogleTranslator(source='iw', target='en').translate(text)
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imgs, descr = text_to_image(text_eng, alpha, K)
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elif detected_language == 'en':
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imgs, descr = text_to_image(text, alpha, K)
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img_files = img_to_file_list(imgs)
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return img_files
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def fake_text(text, alpha):
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en_text = GoogleTranslator(source='iw', target='en').translate(text)
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img , descr = text_to_image(en_text, alpha, K)
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return descr
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with gr.Blocks(width = 300) as demo:
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with gr.Row():
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text = gr.Textbox(
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value = "blue jeans for men",
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label="Enter the product characteristics:"
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)
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alpha = gr.Slider(0, 1, step=0.01, label='Choose alpha:', value = 0.05)
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with gr.Row():
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btn = gr.Button("Generate image")
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with gr.Row():
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gallery = gr.Gallery(
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label="Generated images", show_label=False, elem_id="gallery", columns=[8], rows=[1], object_fit='scale-down', height=160)
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with gr.Row():
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selected = gr.Textbox(label="Product description: ", interactive=False, value = "-----> Description <-------",placeholder="Selected")
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# show the results in gallery on enter key and button press
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text.submit(fake_gan, inputs=[text, alpha], outputs=gallery)
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btn.click(fake_gan, inputs=[text, alpha], outputs=gallery)
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def get_select_index(evt: gr.SelectData,text,alpha):
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eng_text = fake_text(text, alpha)[evt.index]
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#heb_text = GoogleTranslator(source='en', target='iw').translate(eng_text)
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return eng_text
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gallery.select( fn=get_select_index, inputs=[text,alpha], outputs=selected )
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demo.launch(width = 700)
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