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| import gradio as gr | |
| import requests | |
| import os | |
| import PIL | |
| from PIL import Image | |
| from PIL import ImageDraw | |
| from PIL import ImageFont | |
| ##Bloom | |
| API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom" | |
| HF_TOKEN = os.environ["HF_TOKEN"] | |
| headers = {"Authorization": f"Bearer {HF_TOKEN}"} | |
| def write_on_image(final_solution): | |
| print("************ Inside write_on_image ***********") | |
| image_path0 = "./distracted0.jpg" | |
| image0 = Image.open(image_path0) | |
| I1 = ImageDraw.Draw(image0) | |
| myfont = ImageFont.truetype('./font1.ttf', 30) | |
| prompt_list = final_solution.split('\n') | |
| girlfriend = prompt_list[8].split(':')[1].strip() | |
| girlfriend_list = girlfriend.split() | |
| if len(girlfriend_list) >= 2: | |
| girlfriend = '\n'.join(girlfriend_list) | |
| print(f"girlfriend is : {girlfriend }") | |
| new_girl = prompt_list[9].split(':')[1].strip() | |
| new_girl_list = new_girl.split() | |
| if len(new_girl_list) > 2: | |
| new_girl = '\n'.join(new_girl_list) | |
| print(f"new_girl is : {new_girl}") | |
| prompt_list.pop(0) | |
| prompt_list.pop(0) | |
| prompt_list = prompt_list[:8] | |
| prompt_list.append('Distracted from:') | |
| print(f"prompt list is : {prompt_list}") | |
| new_prompt = '\n'.join(prompt_list) | |
| print(f"final_solution is : {new_prompt}") | |
| I1.text((613, 89), girlfriend,font=myfont, fill =(255, 255, 255)) | |
| I1.text((371, 223), "ME", font=myfont, fill =(255, 255, 255)) | |
| I1.text((142, 336), new_girl,font=myfont, fill =(255, 255, 255)) | |
| return image0, new_prompt | |
| def meme_generate(img, prompt, temp, top_p): #prompt, generated_txt): #, input_prompt_sql ): #, input_prompt_dalle2): | |
| print(f"*****Inside meme_generate - Prompt is :{prompt}") | |
| if len(prompt) == 0: | |
| prompt = """Distracted from: homework\nby: side project\nDistracted from: goals\nby: new goals\nDistracted from: working hard\nby: hardly working\nDistracted from: twitter\nby: open in browser\nDistracted from:""" | |
| json_ = {"inputs": prompt, | |
| "parameters": | |
| { | |
| "top_p": top_p, #0.90 default | |
| "max_new_tokens": 64, | |
| "temperature": temp, #1.1 default | |
| "return_full_text": True, | |
| "do_sample": True, | |
| }, | |
| "options": | |
| {"use_cache": True, | |
| "wait_for_model": True, | |
| },} | |
| response = requests.post(API_URL, headers=headers, json=json_) | |
| print(f"Response is : {response}") | |
| output = response.json() | |
| print(f"output is : {output}") | |
| output_tmp = output[0]['generated_text'] | |
| print(f"output_tmp is: {output_tmp}") | |
| solution = output_tmp.split("\nQ:")[0] | |
| print(f"Final response after splits is: {solution}") | |
| meme_image, new_prompt = write_on_image(solution) | |
| return meme_image, new_prompt | |
| demo = gr.Blocks() | |
| with demo: | |
| gr.Markdown("<h1><center>Distracted Boyfriend Meme😄- Using Bloom 🌸 </center></h1>") | |
| gr.Markdown( | |
| """Bloom is a model made by research teams from [HuggingFace](https://huggingface.co/bigscience/bloom) and world over (more than 1000 researchers coming together and working as [BigScienceW Bloom](https://twitter.com/BigscienceW)).Large language models can produce coherent sentences but can they produce **Humor** too? Yes, they can, given the correct prompt (And Yes, Prompt Engineering 🤖 should definitely become a thing by now).\n\n**How to Use this App**: Just Fire Away the Generate Meme button below, as many times as you want!! If you see repeated or similar memes getting generated in consecutive runs, toggle temperature and top_p values.\n\n**How this App works**: Figuring out the right set of Prompting + Writing on an Image + Bit of engineering. Currently, Bloom's Public API has size-limits on Token-Generation, so you can get only few tokens generated at a time.\n\n<pre> Bloom generating very few tokens When Few words are Enough</pre>\n\n<pre><span style='font-size:30px'> 🤝Memes</span></pre>\n\nIt is a fun little App which you can play with for a while.This Space is created by [Yuvraj Sharma](https://twitter.com/yvrjsharma)""" | |
| ) | |
| # <span style="color:green;font-weight:700;font-size:20px">markdown color font styles</span> | |
| with gr.Row(): | |
| in_image = gr.Image(value="./distracted0.jpg", visible=False) | |
| in_image_display = gr.Image(value="./distracted00.jpg", visible=True) | |
| input_prompt = gr.Textbox(label="Write some prompt...", lines=5, visible=False) | |
| output_image = gr.Image() | |
| with gr.Row(): | |
| in_slider_temp = gr.Slider(minimum=0.0, maximum=1.4, value=1.1, step=0.1, label='Temperature') | |
| in_slider_top_p = gr.Slider(minimum=0.50, maximum=0.99, value=0.90, step=0.01, label='Top_p') | |
| b1 = gr.Button("Generate Memes") | |
| b1.click(meme_generate, inputs=[in_image, input_prompt, in_slider_temp, in_slider_top_p] , outputs=[output_image,input_prompt]) | |
| demo.launch(enable_queue=True, debug=True) |