Create app.py

app.py

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+from diffusers import StableDiffusionPipeline
+import torch
+from PIL import Image
+import math
+import gradio as gr
+
+pipeline = StableDiffusionPipeline.from_pretrained("MohamedRashad/diffusion_fashion", torch_dtype=torch.float16)
+
+
+def image_grid(imgs, rows, cols):
+    assert len(imgs) == rows*cols
+
+    w, h = imgs[0].size
+    grid = Image.new('RGB', size=(cols*w, rows*h))
+    grid_w, grid_h = grid.size
+
+    for i, img in enumerate(imgs):
+        grid.paste(img, box=(i%cols*w, i//cols*h))
+    return grid
+
+
+def generate_image2(prompt,num_images):
+ # num_images = 3
+  num_images=math.floor(num_images)
+  prompt = [prompt] * num_images
+  #r=num_images//2
+  #c=2
+  images = pipeline(prompt).images
+  #print(images)
+  grid = image_grid(images, rows=1, cols=num_images)
+
+  grid.save(f"prompt.png")
+  return grid
+
+
+text_input = gr.inputs.Textbox(label="Enter prompt")
+number_input = gr.inputs.Number(label="Enter Number of images")
+
+demo2=gr.Interface(
+    fn=generate_image2,
+    inputs=[text_input, number_input],
+    outputs="image",
+    title="Image Generation",
+    description="Enter a prompt and see a grid of generated images.",
+    layout="vertical",
+)
+
+demo2.launch(inline=False)