add neg prompt, and script

examples/prompts.json

@@ -1,24 +1,23 @@
 {
     "input_1.jpg": [
         "a woman wearing a white top and jeans with a high waist and a high rise heming hem is standing in front of a white background, Christian Hilfgott Brand, waist up, a photocopy, neoclassicism, ultra quality, sharp focus",
-        "blurry"
+        "out of frame, lowres, text, error, cropped, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature"
     ],
     "input_2.jpg": [
         "a woman wearing a black and white sweater and black denim skirt with lace detailing on the sleeves and hem, Annabel Kidston, fine foliage lace, a stipple, rococo",
-        "blurry"
+        "out of frame, lowres, text, error, cropped, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature"
     ],
     "input_3.jpg": [
         "a woman in a pink dress and black jacket walking down a runway with a black jacket on her shoulders, Constance-Anne Parker, fashion, a flemish Baroque, barbizon school",
-        "blurry"
+        "out of frame, lowres, text, error, cropped, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature"
     ],
 
-
     "input_4.jpg": [
         "a man in a tuxedo and bow tie at an oscars event with a red carpet and white wall, Americo Makk, full length, a marble sculpture, tachisme",
-        "blurry"
+        "out of frame, lowres, text, error, cropped, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature"
     ],
     "input_5.jpg": [
         "a woman in a dress standing next to a chair and a chair with a chair in front of it, Christian Hilfgott Brand, hourglass slim figure, a digital rendering, american barbizon school",
-        "blurry"
+        "out of frame, lowres, text, error, cropped, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, out of frame, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, username, watermark, signature"
     ]
 }

src/inference_no_condition.py

@@ -0,0 +1,34 @@
+import json
+
+from diffusers import DiffusionPipeline
+import torch
+import matplotlib.pyplot as plt
+
+
+pipe = DiffusionPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0",
+    torch_dtype=torch.float16,
+    use_safetensors=True,
+    variant="fp16",
+)
+
+pipe.to("cuda")
+
+with open('../examples/prompts.json', 'r') as f:
+    prompts_list = list(json.load(f).values())
+
+image_index = 0
+prompt, negative_prompt = prompts_list[image_index]
+
+images = pipe(
+    prompt=prompt,
+    height=1024,
+    width=1024,
+    negative_prompt=negative_prompt,
+    seed=0,
+    num_inference_steps=20,
+    guidance_scale=9.0,
+).images[0]
+
+plt.imshow(images)
+plt.show()