rhfeiyang commited on
Commit
b743ad0
1 Parent(s): 5fc7aea
Files changed (2) hide show
  1. hf_demo.py +16 -10
  2. hf_demo_test.ipynb +1 -1
hf_demo.py CHANGED
@@ -45,7 +45,7 @@ def demo_inference_gen_artistic(adapter_choice:str, prompt:str, seed:int=0, step
45
  style_prompt=None
46
  prompts = [prompt]
47
  infer_loader = get_validation_dataloader(prompts,num_workers=0)
48
- network = get_lora_network(pipe.unet, adapter_path, weight_dtype=dtype)["network"]
49
 
50
  pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,
51
  height=512, width=512, scales=[adapter_scale],
@@ -59,7 +59,7 @@ def demo_inference_gen_ori( prompt:str, seed:int=0, steps=50, guidance_scale=7.5
59
  style_prompt=None
60
  prompts = [prompt]
61
  infer_loader = get_validation_dataloader(prompts,num_workers=0)
62
- network = get_lora_network(pipe.unet, "None", weight_dtype=dtype)["network"]
63
 
64
  pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,
65
  height=512, width=512, scales=[0.0],
@@ -75,7 +75,7 @@ def demo_inference_stylization_ori(ref_image, prompt:str, seed:int=0, steps=50,
75
  prompts = [prompt]
76
  # convert np to pil
77
  ref_image = [Image.fromarray(ref_image)]
78
- network = get_lora_network(pipe.unet, "None", weight_dtype=dtype)["network"]
79
  infer_loader = get_validation_dataloader(prompts, ref_image,num_workers=0)
80
  pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,
81
  height=512, width=512, scales=[0.0],
@@ -95,7 +95,7 @@ def demo_inference_stylization_artistic(ref_image, adapter_choice:str, prompt:st
95
  prompts = [prompt]
96
  # convert np to pil
97
  ref_image = [Image.fromarray(ref_image)]
98
- network = get_lora_network(pipe.unet, adapter_path, weight_dtype=dtype)["network"]
99
  infer_loader = get_validation_dataloader(prompts, ref_image,num_workers=0)
100
  pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,
101
  height=512, width=512, scales=[adapter_scale],
@@ -105,7 +105,7 @@ def demo_inference_stylization_artistic(ref_image, adapter_choice:str, prompt:st
105
  return pred_images
106
 
107
  @spaces.GPU
108
- def demo_inference_all(prompt:str, ref_image, adapter_choice="Andre Derain (fauvism)", seed:int=0, steps=20, guidance_scale=7.5, adapter_scale=1.0,start_noise=800):
109
  results = []
110
  results.append(demo_inference_gen_ori(prompt, seed, steps, guidance_scale))
111
  results.append(demo_inference_gen_artistic(adapter_choice, prompt, seed, steps, guidance_scale, adapter_scale))
@@ -126,7 +126,7 @@ with block:
126
  max_lines=10,
127
  placeholder="Enter your prompt (long and detailed would be better)",
128
  container=True,
129
- value="a black SUV driving down a highway with a scenic view of mountains and water in the background. The SUV is the main focus of the image, and it appears to be traveling at a moderate speed. The road is well-maintained and provides a smooth driving experience. The mountains and water create a picturesque backdrop, adding to the overall beauty of the scene. The image captures the essence of a leisurely road trip, with the SUV as the primary subject, highlighting the sense of adventure and exploration that comes with such journeys.",
130
  )
131
 
132
  with gr.Tab('Generation'):
@@ -242,27 +242,32 @@ with block:
242
  examples=[
243
  ["Snow-covered trees with sunlight shining through",
244
  "data/Snow-covered_trees_with_sunlight_shining_through.jpg",
 
245
  ],
246
  ["A picturesque landscape showcasing a winding river cutting through a lush green valley, surrounded by rugged mountains under a clear blue sky. The mix of red and brown tones in the rocky hills adds to the region's natural beauty and diversity.",
247
  "data/0011772.jpg",
 
248
  ],
249
- ["a black SUV driving down a highway with a scenic view of mountains and water in the background. The SUV is the main focus of the image, and it appears to be traveling at a moderate speed. The road is well-maintained and provides a smooth driving experience. The mountains and water create a picturesque backdrop, adding to the overall beauty of the scene. The image captures the essence of a leisurely road trip, with the SUV as the primary subject, highlighting the sense of adventure and exploration that comes with such journeys.",
250
  "data/a_black_SUV_driving_down_a_highway_with_a_scenic_view_of_mountains_and_water_in_the_background._The_.jpg",
 
251
  ],
252
- ["a beautiful garden with a large pond. The pond is surrounded by a wooden deck, and there are several chairs placed around the area. A stone fountain is present in the middle of the pond, adding to the serene atmosphere. The garden is decorated with a variety of potted plants, creating a lush and inviting environment. The scene is captured in a vibrant and colorful style, highlighting the natural beauty of the garden.",
253
- "data/a_beautiful_garden_with_a_large_pond._The_pond_is_surrounded_by_a_wooden_deck,_and_there_are_several.jpg"
 
254
  ],
255
  [
256
  "A blue bench situated in a park, surrounded by trees and leaves. The bench is positioned under a tree, providing shade and a peaceful atmosphere. There are several benches in the park, with one being closer to the foreground and the others further in the background. A person can be seen in the distance, possibly enjoying the park or taking a walk. The overall scene is serene and inviting, with the bench serving as a focal point in the park's landscape.",
257
  "data/003904765.jpg",
 
258
  ]
259
 
260
  ],
261
  inputs=[
262
  text,
263
  gallery_stylization_ref,
264
- adapter_choice,
265
  seed,
 
266
  steps,
267
  scale,
268
  adapter_scale,
@@ -272,5 +277,6 @@ with block:
272
  outputs=[gallery_gen_ori, gallery_gen_art, gallery_stylization_ori, gallery_stylization_art],
273
  cache_examples=True,
274
  )
 
275
  block.launch()
276
  # block.launch(sharing=True)
 
45
  style_prompt=None
46
  prompts = [prompt]
47
  infer_loader = get_validation_dataloader(prompts,num_workers=0)
48
+ network = get_lora_network(pipe.unet, adapter_path, weight_dtype=dtype, device=device)["network"]
49
 
50
  pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,
51
  height=512, width=512, scales=[adapter_scale],
 
59
  style_prompt=None
60
  prompts = [prompt]
61
  infer_loader = get_validation_dataloader(prompts,num_workers=0)
62
+ network = get_lora_network(pipe.unet, "None", weight_dtype=dtype, device=device)["network"]
63
 
64
  pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,
65
  height=512, width=512, scales=[0.0],
 
75
  prompts = [prompt]
76
  # convert np to pil
77
  ref_image = [Image.fromarray(ref_image)]
78
+ network = get_lora_network(pipe.unet, "None", weight_dtype=dtype, device=device)["network"]
79
  infer_loader = get_validation_dataloader(prompts, ref_image,num_workers=0)
80
  pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,
81
  height=512, width=512, scales=[0.0],
 
95
  prompts = [prompt]
96
  # convert np to pil
97
  ref_image = [Image.fromarray(ref_image)]
98
+ network = get_lora_network(pipe.unet, adapter_path, weight_dtype=dtype, device=device)["network"]
99
  infer_loader = get_validation_dataloader(prompts, ref_image,num_workers=0)
100
  pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,
101
  height=512, width=512, scales=[adapter_scale],
 
105
  return pred_images
106
 
107
  @spaces.GPU
108
+ def demo_inference_all(prompt:str, ref_image, seed:int=0, adapter_choice="Andre Derain (fauvism)", steps=20, guidance_scale=7.5, adapter_scale=1.0,start_noise=800):
109
  results = []
110
  results.append(demo_inference_gen_ori(prompt, seed, steps, guidance_scale))
111
  results.append(demo_inference_gen_artistic(adapter_choice, prompt, seed, steps, guidance_scale, adapter_scale))
 
126
  max_lines=10,
127
  placeholder="Enter your prompt (long and detailed would be better)",
128
  container=True,
129
+ value="A beautiful garden with a large pond. The pond is surrounded by a wooden deck, and there are several chairs placed around the area. A stone fountain is present in the middle of the pond, adding to the serene atmosphere. The garden is decorated with a variety of potted plants, creating a lush and inviting environment. The scene is captured in a vibrant and colorful style, highlighting the natural beauty of the garden.",
130
  )
131
 
132
  with gr.Tab('Generation'):
 
242
  examples=[
243
  ["Snow-covered trees with sunlight shining through",
244
  "data/Snow-covered_trees_with_sunlight_shining_through.jpg",
245
+ 0,
246
  ],
247
  ["A picturesque landscape showcasing a winding river cutting through a lush green valley, surrounded by rugged mountains under a clear blue sky. The mix of red and brown tones in the rocky hills adds to the region's natural beauty and diversity.",
248
  "data/0011772.jpg",
249
+ 528741066,
250
  ],
251
+ ["A black SUV driving down a highway with a scenic view of mountains and water in the background. The SUV is the main focus of the image, and it appears to be traveling at a moderate speed. The road is well-maintained and provides a smooth driving experience. The mountains and water create a picturesque backdrop, adding to the overall beauty of the scene. The image captures the essence of a leisurely road trip, with the SUV as the primary subject, highlighting the sense of adventure and exploration that comes with such journeys.",
252
  "data/a_black_SUV_driving_down_a_highway_with_a_scenic_view_of_mountains_and_water_in_the_background._The_.jpg",
253
+ 98762568,
254
  ],
255
+ ["A beautiful garden with a large pond. The pond is surrounded by a wooden deck, and there are several chairs placed around the area. A stone fountain is present in the middle of the pond, adding to the serene atmosphere. The garden is decorated with a variety of potted plants, creating a lush and inviting environment. The scene is captured in a vibrant and colorful style, highlighting the natural beauty of the garden.",
256
+ "data/a_beautiful_garden_with_a_large_pond._The_pond_is_surrounded_by_a_wooden_deck,_and_there_are_several.jpg",
257
+ 76265772,
258
  ],
259
  [
260
  "A blue bench situated in a park, surrounded by trees and leaves. The bench is positioned under a tree, providing shade and a peaceful atmosphere. There are several benches in the park, with one being closer to the foreground and the others further in the background. A person can be seen in the distance, possibly enjoying the park or taking a walk. The overall scene is serene and inviting, with the bench serving as a focal point in the park's landscape.",
261
  "data/003904765.jpg",
262
+ 3904764,
263
  ]
264
 
265
  ],
266
  inputs=[
267
  text,
268
  gallery_stylization_ref,
 
269
  seed,
270
+ adapter_choice,
271
  steps,
272
  scale,
273
  adapter_scale,
 
277
  outputs=[gallery_gen_ori, gallery_gen_art, gallery_stylization_ori, gallery_stylization_art],
278
  cache_examples=True,
279
  )
280
+
281
  block.launch()
282
  # block.launch(sharing=True)
hf_demo_test.ipynb CHANGED
@@ -134,7 +134,7 @@
134
  " style_prompt=None\n",
135
  " prompts = [prompt]\n",
136
  " infer_loader = get_validation_dataloader(prompts,num_workers=0)\n",
137
- " network = get_lora_network(pipe.unet, adapter_path, weight_dtype=dtype)[\"network\"]\n",
138
  "\n",
139
  " pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,\n",
140
  " height=512, width=512, scales=[adapter_scale],\n",
 
134
  " style_prompt=None\n",
135
  " prompts = [prompt]\n",
136
  " infer_loader = get_validation_dataloader(prompts,num_workers=0)\n",
137
+ " network = get_lora_network(pipe.unet, adapter_path, weight_dtype=dtype, device=device)[\"network\"]\n",
138
  "\n",
139
  " pred_images = inference(network, pipe.tokenizer, pipe.text_encoder, pipe.vae, pipe.unet, pipe.scheduler, infer_loader,\n",
140
  " height=512, width=512, scales=[adapter_scale],\n",