Update app.py

app.py

@@ -41,29 +41,45 @@ clip, processor = ruclip.load('ruclip-vit-base-patch32-384', device=device)
 clip_predictor = ruclip.Predictor(clip, processor, device, bs=8)
 text = 'радуга на фоне ночного города'
 
+#seed_everything(42)
+#pil_images = []
+#scores = []
+#for top_k, top_p, images_num in [
+#    (2048, 0.995, 6),
+#]:
+#    _pil_images, _scores = generate_images(text, tokenizer, model, vae, top_k=top_k, images_num=images_num, #bs=8, top_p=top_p)
+#    pil_images += _pil_images
+#    scores += _scores
+
+def model(text, tokenizer=tokenizer, dalle=dalle, vae=vae, top_k=2048, images_num=1, bs=8, top_p=0.995):
+    # _pil_images, _scores = generate_images(text, tokenizer, dalle, vae, top_k=top_k, images_num=images_num, bs=8, top_p=top_p)
+    pil_images = generate_images(text, tokenizer, dalle, vae, top_k=top_k, images_num=images_num, bs=8, top_p=top_p)
+    pil_images = pil_images[0]
+    return pil_images
+
 seed_everything(42)
 pil_images = []
 scores = []
-for top_k, top_p, images_num in [
-    (2048, 0.995, 6),
-]:
-    _pil_images, _scores = generate_images(text, tokenizer, model, vae, top_k=top_k, images_num=images_num, bs=8, top_p=top_p)
-    pil_images += _pil_images
-    scores += _scores
+top_k = 2048
+top_p = 0.995
+images_num = 1
+
+iface = gr.Interface(fn=model, 
+  inputs=[gr.inputs.Textbox(label="Text prompt"),
+  outputs=[gr.outputs.Image(type="pil", label="Generated Image")]).launch()
 
-#show(pil_images, 6)
 #TEST--------
 
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+#pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
 
-def predict(image):
-  predictions = pipeline(image)
-  return {p["label"]: p["score"] for p in predictions}
+#def predict(image):
+#  predictions = pipeline(image)
+#  return {p["label"]: p["score"] for p in predictions}
 
-gr.Interface(
-    predict,
-    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
-    outputs=gr.outputs.Label(num_top_classes=2),
-    title="Hot Dog? Or Not?",
-).launch() 
+#gr.Interface(
+#    predict,
+#    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
+#    outputs=gr.outputs.Label(num_top_classes=2),
+#    title="Hot Dog? Or Not?",
+#).launch()