norm

app.py

@@ -223,18 +223,29 @@ def sample_ddpm(n_sample, save_rate=20):
 
 def greet(input):
 	steps = int(input)
-	#samples, intermediate = sample_ddim(32, n=steps)
+	samples, intermediate = sample_ddim(32, n=steps)
 	#ctx = F.one_hot(torch.randint(0, 5, (32,)), 5).to(device=device).float()
 	#samples, intermediate = sample_ddim_context(32, ctx, steps)
-	samples, intermediate = sample_ddpm(steps)
+	#samples, intermediate = sample_ddpm(steps)
 	#response = transform2(transform(np.moveaxis(samples.detach().cpu().numpy(),1,3)[-1]))
 	#response2 = transform2(transform(np.moveaxis(samples.detach().cpu().numpy(),1,3)[1]))
 	#response = im.fromarray(intermediate[24][0][1]).convert("RGB")
+
+	sx_gen_store = np.moveaxis(intermediate,2,4)
+	nsx_gen_store = norm_all(sx_gen_store, sx_gen_store.shape[0], 32)
+
 	response = intermediate.shape;
-	response2 = transform2(transform(np.moveaxis(intermediate,2,4)[0][0]))
-	response3 = transform2(transform(np.moveaxis(intermediate,2,4)[int(steps/2)][0]))
-	response4 = transform2(transform(np.moveaxis(intermediate,2,4)[int(steps/4)][0]))
-	response5 = transform2(transform(np.moveaxis(intermediate,2,4)[-1][0]))
+	response2 = transform2(transform(nsx_gen_store[0][0]))
+	response3 = transform2(transform(nsx_gen_store[int(steps/2)][0]))
+	response4 = transform2(transform(nsx_gen_store[int(steps/4)][0]))
+	response5 = transform2(transform(nsx_gen_store[-1][0]))
+
+
+	#response = intermediate.shape;
+	#response2 = transform2(transform(np.moveaxis(intermediate,2,4)[0][0]))
+	#response3 = transform2(transform(np.moveaxis(intermediate,2,4)[int(steps/2)][0]))
+	#response4 = transform2(transform(np.moveaxis(intermediate,2,4)[int(steps/4)][0]))
+	#response5 = transform2(transform(np.moveaxis(intermediate,2,4)[-1][0]))
 
 	return response, response2, response3, response4, response5
 
@@ -245,6 +256,6 @@ transform2 = transforms.ToPILImage()
 
 #iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Text to find entities", lines=2)], outputs=[gr.HighlightedText(label="Text with entities")], title="NER with dslim/bert-base-NER", description="Find entities using the `dslim/bert-base-NER` model under the hood!", allow_flagging="never", examples=["My name is Andrew and I live in California", "My name is Poli and work at HuggingFace"])
 #iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Co-Retailing Business")], outputs=[gr.outputs.Image(type="pil", width=64, label="Output Image"), gr.outputs.Image(type="pil", width=64, label="Output Image2"), gr.outputs.Image(type="pil", width=64, label="Output Image3"), gr.outputs.Image(type="pil", width=64, label="Output Image4")])
-iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="steps", value=500)], outputs=[gr.Textbox(label="Info"), gr.Image(type="pil", width=64, label="Output Image"), gr.Image(type="pil", width=64, label="Output Image2"), gr.Image(type="pil", width=64, label="Output Image3"), gr.Image(type="pil", width=64, label="Output Image4")])
+iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="steps", value=20)], outputs=[gr.Textbox(label="Info"), gr.Image(type="pil", width=64, label="Output Image"), gr.Image(type="pil", width=64, label="Output Image2"), gr.Image(type="pil", width=64, label="Output Image3"), gr.Image(type="pil", width=64, label="Output Image4")])
 #iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Co-Retailing Business")], outputs=[gr.Textbox()])
 iface.launch()