Update app.py

app.py

@@ -8,7 +8,6 @@ import gradio as gr
 import base64
 from io import BytesIO
 # from fastapi import FastAPI
-from PIL import ImageOps
 from PIL import Image
 import torch as th
 
@@ -113,13 +112,11 @@ print('total upsampler parameters', sum(x.numel() for x in model_up.parameters()
 
 
 
-def get_images(batch: th.Tensor, output_size=(256, 256)):
+def get_images(batch: th.Tensor):
     """ Display a batch of images inline. """
     scaled = ((batch + 1)*127.5).round().clamp(0,255).to(th.uint8).cpu()
     reshaped = scaled.permute(2, 0, 3, 1).reshape([batch.shape[2], -1, 3])
-    image = Image.fromarray(reshaped.numpy())
-    image = ImageOps.fit(image, output_size, Image.ANTIALIAS)
-    return image
+    return Image.fromarray(reshaped.numpy())
 
 
     
@@ -236,10 +233,9 @@ def sample(prompt):
     )[:batch_size]
     model_up.del_cache()
 
-    # Show the output
     image = get_images(up_samples)
-    image = to_base64(image)
-    #return {"image": image}
+    # image = to_base64(image)
+    # return {"image": image}
     return image
 
 
@@ -249,6 +245,8 @@ title = "Interactive demo: glide-text2im dermoscopic image generator"
 description = "Demo for the Finetuned version of OpenAI's GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. Please be aware that generation of the image will take up to 20 minutes, as CPU is used for the generation. Please cite our research paper with the title -Finetuning of GLIDE stable diffusion model for AI-based text-conditional image synthesis of dermoscopic images-"
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2112.10741'>GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models</a> | <a href='https://github.com/openai/glide-text2im/'>Official Repo</a></p>"
 examples =["melanoma"]
+css = ".output_image {height: 40rem !important; width: 100% !important;}"
+
 
 iface = gr.Interface(fn=sample, 
                      inputs=gr.inputs.Textbox(label='Which dermoscopic entity would you like to see? Choose one of the following one: "melanoma", "melanocytic nevi", "Actinic keratoses and intraepithelial carcinoma / Bowen disease, "benign keratosis-like lesions (solar lentigines / seborrheic keratoses and lichen-planus like keratoses", "basal cell carcinoma", "dermatofibroma", "vascular lesions"'), 
@@ -257,5 +255,6 @@ iface = gr.Interface(fn=sample,
                      description=description,
                      article=article,
                      examples=examples,
+                     css=css,
                      enable_queue=True)
 iface.launch(debug=True)