running space

app.py

@@ -6,49 +6,33 @@ from io import BytesIO
 from diffusers import StableDiffusionImg2ImgPipeline
 
 device = "cpu"
-model_id = "pwc-india/tartan_weights"
-pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to(device)
+#model_path = "weights"
+#model_id_or_path = "runwayml/stable-diffusion-v1-5"
 
-pipe2 = StableDiffusionImg2ImgPipeline(**pipe.components).to(device)
+model_id = "rikdas/weights"
+pipe = StableDiffusionPipeline.from_pretrained(model_id).to(device)
+
+pipe2 = StableDiffusionImg2ImgPipeline.from_pretrained(model_id).to(device)
 
 import gradio as gr
 
-def generate_txt2img(inp_txt, inp_neg, num_inf_steps, width, height, g_scale, num_imgs):
-    return pipe(prompt=inp_txt, negative_prompt=inp_neg, num_inference_steps=num_inf_steps, width=width, height=height, guidance_scale=g_scale, num_images_per_prompt=num_imgs).images
-def generate_img2img(inp_img, inp_txt, inp_neg, num_inf_steps, g_scale, num_imgs, strength):
-    image = Image.fromarray(inp_img)
-    image = image.resize((512, 512))
-    return pipe2(prompt=inp_txt, negative_prompt=inp_neg, num_inference_steps=num_inf_steps, image=image, strength=strength, guidance_scale=g_scale, num_images_per_prompt=num_imgs).images
+def generate_txt2img(prompt):
+    return pipe(prompt, num_inference_steps=25, guidance_scale=7.5).images[0]
+def generate_img2img(img, prompt):
+    image = Image.fromarray(img)
+    return pipe2(prompt=prompt, image=image, strength=0.75, guidance_scale=7.5).images[0]
 
 with gr.Blocks() as demo:
     with gr.Tab("Text2Image"):
-        with gr.Group():
-            inp_txt = gr.Text(show_label=False, placeholder="Enter your prompt here...")
-            inp_neg = gr.Text(show_label=False, placeholder="Enter your negative prompt here...")
-            with gr.Accordion("Extra parameters", open=False):
-                num_inf_steps = gr.Slider(label="Number of inference steps", minimum=20, maximum=100, value=50, step=1)
-                with gr.Row():
-                    with gr.Column():
-                        width = gr.Slider(label="Width(pixels)", minimum=256, maximum=1024, value=512, step=1)
-                    with gr.Column():
-                        height = gr.Slider(label="Height(pixels)", minimum=256, maximum=1024, value=512, step=1)
-                g_scale = gr.Slider(label="Guidance scale", minimum=1, maximum=10, value=7.5, step=0.5)
-                num_imgs = gr.Slider(label="Number of images", minimum=1, maximum=10, value=1, step=1)
-            btn = gr.Button("Generate")
-        out_img = gr.Gallery(preview=True)
-        btn.click(fn=generate_txt2img, inputs=[inp_txt, inp_neg, num_inf_steps, width, height, g_scale, num_imgs], outputs=[out_img])
+        inp_txt = gr.Text(showlabel=False, placeholder="Enter your prompt here...")
+        btn = gr.Button("Generate")
+        out_img = gr.Image()
+        btn.click(fn=generate_txt2img, inputs=[inp_txt], outputs=[out_img])
     with gr.Tab("Image2Image"):
-        with gr.Group():
-            inp_img = gr.Image()
-            inp_txt2 = gr.Text(show_label=False, placeholder="Enter your prompt here...")
-            inp_neg2 = gr.Text(show_label=False, placeholder="Enter your negative prompt here...")
-            with gr.Accordion("Extra parameters", open=False):
-                num_inf_steps2 = gr.Slider(label="Number of inference steps", minimum=20, maximum=100, value=50, step=1)
-                g_scale2 = gr.Slider(label="Guidance scale", minimum=1, maximum=10, value=7.5, step=0.5)
-                num_imgs2 = gr.Slider(label="Number of images", minimum=1, maximum=10, value=1, step=1)
-                strength = gr.Slider(label="Strength", minimum=0, maximum=1, value=0.8, step=0.1)
-            btn2 = gr.Button("Generate")
-        out_img2 = gr.Gallery(preview=True)
-        btn2.click(fn=generate_img2img, inputs=[inp_img, inp_txt2, inp_neg2, num_inf_steps2, g_scale2, num_imgs2, strength], outputs=[out_img2])
-
+        inp_img = gr.Image()
+        inp_txt2 = gr.Text(showlabel=False,placeholder="Enter your prompt here...")
+        btn2 = gr.Button("Generate")
+        out_img2 = gr.Image()
+        btn2.click(fn=generate_img2img, inputs=[inp_img, inp_txt2], outputs=[out_img2])
+        
 demo.launch(debug=True)