Update app.py

app.py

@@ -1,4 +1,5 @@
 import gradio as gr
+import numpy as np
 import torch
 import torchvision.transforms as transforms
 from sentence_transformers import SentenceTransformer, util
@@ -9,6 +10,22 @@ import random
 import torch
 import torch.nn as nn
 from generatorModel import Generator
+import cv2
+
+def upscale_and_sharpen_image(input_array):
+    # Upscale the image to 256x256
+    upscaled_img = cv2.resize(input_array, (256, 256), interpolation=cv2.INTER_LANCZOS4)
+
+    # Define a sharpening kernel
+    sharpening_kernel = np.array([[-1, -1, -1],
+                                  [-1, 9, -1],
+                                  [-1, -1, -1]])
+
+    # Apply the sharpening kernel using filter2D
+    sharpened_img = cv2.filter2D(upscaled_img, -1, sharpening_kernel)
+
+    # Return the processed array
+    return sharpened_img
 
 def load_embedding(model):
     # Load your model and other components here
@@ -52,7 +69,7 @@ def generate_image(caption):
     fake_images = generator(noise, embeddings[sampled_item].unsqueeze(0).unsqueeze(0))
     img = fake_images.squeeze(0).permute(1, 2, 0).cpu().detach().numpy()
     img = (img - img.min()) / (img.max() - img.min())
-
+    img = upscale_and_sharpen_image(img)
     return img
 
 noise_dim = 16