Duplicate from imseldrith/text2image

Co-authored-by: Ashiq Hussain <imseldrith@users.noreply.huggingface.co>

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README.md

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+---
+title: Text2image
+emoji: ⚡
+colorFrom: gray
+colorTo: purple
+sdk: gradio
+sdk_version: 3.12.0
+app_file: app.py
+pinned: false
+license: openrail
+duplicated_from: imseldrith/text2image
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import torch
+from torch import autocast
+from diffusers import StableDiffusionPipeline, PNDMScheduler
+import requests
+import PIL
+from PIL import Image
+import numpy as np
+from io import BytesIO
+from diffusers import StableDiffusionImg2ImgPipeline
+
+def preprocess(image):
+    w, h = image.size
+    w, h = map(lambda x: x - x % 32, (w, h))  # resize to integer multiple of 32
+    image = image.resize((w, h), resample=PIL.Image.LANCZOS)
+    image = np.array(image).astype(np.float32) / 255.0
+    image = image[None].transpose(0, 3, 1, 2)
+    image = torch.from_numpy(image)
+    return 2.0 * image - 1.0
+
+scheduler_ = PNDMScheduler(
+    beta_start=0.005, 
+    beta_end=0.12, 
+    beta_schedule="scaled_linear"
+)
+
+pipe = StableDiffusionPipeline.from_pretrained(
+    "CompVis/stable-diffusion-v1-4", 
+    scheduler=scheduler_,
+    revision="fp16", 
+    use_auth_token=True
+).to("cuda")
+
+pipeimg = StableDiffusionImg2ImgPipeline.from_pretrained(
+    "CompVis/stable-diffusion-v1-4",
+    revision="fp16", 
+    torch_dtype=torch.float16,
+    use_auth_token=True
+).to("cuda")
+
+block = gr.Blocks(css=".container { max-width: 800px; margin: auto; }")
+
+num_samples = 2
+
+def infer(prompt, init_image, strength):
+    if init_image != None:
+        init_image = init_image.resize((512, 512))
+        init_image = preprocess(init_image)
+        with autocast("cuda"):
+            images = pipeimg([prompt] * num_samples, init_image=init_image, strength=strength, guidance_scale=7.5)["sample"]
+    else: 
+        with autocast("cuda"):
+            images = pipe([prompt] * num_samples, guidance_scale=7.5)["sample"]
+
+    return images
+
+
+with block as demo:
+    gr.Markdown("<h1><center>Stable Diffusion</center></h1>")
+    gr.Markdown(
+        "Stable Diffusion is an AI model that generates images from any prompt you give!"
+    )
+    with gr.Group():
+        with gr.Box():
+            with gr.Row().style(mobile_collapse=False, equal_height=True):
+
+                text = gr.Textbox(
+                    label="Enter your prompt", show_label=False, max_lines=1
+                ).style(
+                    border=(True, False, True, True),
+                    rounded=(True, False, False, True),
+                    container=False,
+                )
+                btn = gr.Button("Run").style(
+                    margin=False,
+                    rounded=(False, True, True, False),
+                )
+        strength_slider = gr.Slider(
+            label="Strength",
+            maximum = 1,
+            value = 0.75         
+        )
+        image = gr.Image(
+            label="Intial Image",
+            type="pil"
+        )
+               
+        gallery = gr.Gallery(label="Generated images", show_label=False).style(
+            grid=[2], height="auto"
+        )
+        text.submit(infer, inputs=[text,image,strength_slider], outputs=gallery)
+        btn.click(infer, inputs=[text,image,strength_slider], outputs=gallery)
+
+    gr.Markdown(
+        """___
+   <p style='text-align: center'>
+   Created by CompVis and Stability AI
+   <br/>
+   </p>"""
+    )
+
+
+demo.launch(share=True)

requirements.txt

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+gradio
+torch
+diffusers
+requests
+numpy