add app file

app.py

@@ -0,0 +1,65 @@
+import math
+import torch
+import torchvision
+import gradio as gr
+from PIL import Image
+import torchvision
+from test_ddgan import load_model, sample
+from model_configs import get_model_config
+from huggingface_hub import hf_hub_download
+
+def download(filename):
+    return "models/" + filename
+
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+models = {
+    "diffusion_db_128ch_1timesteps_openclip_vith14": load_model(get_model_config('ddgan_ddb_v2'), download('diffusion_db_128ch_1timesteps_openclip_vith14.th'), device=device),
+    "diffusion_db_192ch_2timesteps_openclip_vith14": load_model(get_model_config('ddgan_ddb_v3'), download('diffusion_db_192ch_2timesteps_openclip_vith14.th'), device=device),
+}
+default = "diffusion_db_128ch_1timesteps_openclip_vith14"
+
+def gen(md, model_name, md2, text, seed, nb_samples, width, height):
+    torch.manual_seed(int(seed))
+    model = models[model_name]
+    nb_samples = int(nb_samples)
+    height = int(height)
+    width =  int(width)
+    with torch.no_grad():
+        cond = model.text_encoder([text]*nb_samples)
+        if text == "":
+            cond[0].normal_()
+            cond[1].normal_()
+            cond[0][1:] = cond[0][0:1]
+            cond[1][1:] = cond[1][0:1]
+            
+        x_init = torch.randn(nb_samples, 3, height, width).to(device)
+        fake_sample = sample(model, x_init=x_init, cond=cond)
+        fake_sample = (fake_sample + 1) / 2
+    grid = torchvision.utils.make_grid(fake_sample, nrow=4)
+    grid = grid.permute(1, 2, 0).cpu().numpy()
+    grid = (grid*255).astype("uint8")
+    return Image.fromarray(grid)
+
+text = """
+DDGAN
+"""
+iface = gr.Interface(
+    fn=gen,
+    inputs=[
+        gr.Markdown(text),
+        # text caption
+        gr.Dropdown(list(models.keys()), value=default), 
+        gr.Markdown("If text caption is empty, random CLIP embeddings will be used as input"),
+        gr.Textbox(
+            lines=1, 
+            placeholder="Enter text caption here, or leave empty", 
+            value="Painting of a hamster king  with a crown and a cape  in a magical forest."
+        ),
+        gr.Number(value=0), # seed
+        gr.Number(value=4), # nb_samples
+        gr.Number(value=256), # width
+        gr.Number(value=256),# height
+    ],
+    outputs="image"
+)
+iface.launch()