Duplicate from jmourad/TXT2IMG-MJ-Desc

Co-authored-by: Rafael Mourad <[email protected]>

.gitattributes

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README.md

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+---
+title: TXT2IMG MJ Desc
+emoji: 🔥
+colorFrom: gray
+colorTo: gray
+sdk: gradio
+sdk_version: 3.24.1
+app_file: app.py
+pinned: false
+license: artistic-2.0
+duplicated_from: jmourad/TXT2IMG-MJ-Desc
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+# Importar bibliotecas
+import torch
+import re
+import random
+import requests
+import shutil
+from clip_interrogator import Config, Interrogator
+from transformers import pipeline, set_seed, AutoTokenizer, AutoModelForSeq2SeqLM
+from PIL import Image
+import gradio as gr
+
+# Configurar CLIP
+config = Config()
+config.device = 'cuda' if torch.cuda.is_available() else 'cpu'
+config.blip_offload = False if torch.cuda.is_available() else True
+config.chunk_size = 2048
+config.flavor_intermediate_count = 512
+config.blip_num_beams = 64
+config.clip_model_name = "ViT-H-14/laion2b_s32b_b79k"
+ci = Interrogator(config)
+
+# Función para generar prompt desde imagen
+def get_prompt_from_image(image, mode):
+    image = image.convert('RGB')
+    if mode == 'best':
+        prompt = ci.interrogate(image)
+    elif mode == 'classic':
+        prompt = ci.interrogate_classic(image)
+    elif mode == 'fast':
+        prompt = ci.interrogate_fast(image)
+    elif mode == 'negative':
+        prompt = ci.interrogate_negative(image)
+    return prompt
+
+# Función para generar texto
+text_pipe = pipeline('text-generation', model='succinctly/text2image-prompt-generator')
+
+def text_generate(input):
+    seed = random.randint(100, 1000000)
+    set_seed(seed)
+    for count in range(6):    
+        sequences = text_pipe(input, max_length=random.randint(60, 90), num_return_sequences=8)
+        list = []
+        for sequence in sequences:
+            line = sequence['generated_text'].strip()
+            if line != input and len(line) > (len(input) + 4) and line.endswith((':', '-', '—')) is False:
+                list.append(line)
+
+        result = "\n".join(list)
+        result = re.sub('[^ ]+\.[^ ]+','', result)
+        result = result.replace('<', '').replace('>', '')
+        if result != '':
+            return result
+        if count == 5:
+            return result
+
+# Crear interfaz gradio
+with gr.Blocks() as block:
+    with gr.Column():
+        gr.HTML('<h1>MidJourney / SD2 Helper Tool</h1>')
+        with gr.Tab('Generate from Image'):
+            with gr.Row():
+                input_image = gr.Image(type='pil')
+                with gr.Column():
+                    input_mode = gr.Radio(['best', 'fast', 'classic', 'negative'], value='best', label='Mode')
+            img_btn = gr.Button('Discover Image Prompt')
+            output_image = gr.Textbox(lines=6, label='Generated Prompt')
+
+        with gr.Tab('Generate from Text'):
+            input_text = gr.Textbox(lines=6, label='Your Idea', placeholder='Enter your content here...')
+            output_text = gr.Textbox(lines=6, label='Generated Prompt')
+            text_btn = gr.Button('Generate Prompt')
+
+    img_btn.click(fn=get_prompt_from_image, inputs=[input_image, input_mode], outputs=output_image)
+    text_btn.click(fn=text_generate, inputs=input_text, outputs=output_text)
+
+block.queue(max_size=64).launch(show_api=False, enable_queue=True, debug=True, share=False, server_name='0.0.0.0')

requirements.txt

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+transformers
+gradio
+clip_interrogator
+torch