jkorstad commited on
Commit
97e83fa
·
verified ·
1 Parent(s): b00ccd0

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +90 -88
app.py CHANGED
@@ -110,91 +110,93 @@ col-container {
110
  """
111
 
112
  with gr.Blocks(css=css) as demo:
113
-
114
- with gr.Column(elem_id="col-container"):
115
- gr.Markdown(f"""Generate an image with Flux. Try it out and let me know what you think! Expect roughly 45-60 seconds per generation with it's current backend. This can be scaled up over time as needed. Thanks!
116
- Not for Commercial Use - Apache 2.0 License
117
- """)
118
-
119
- with gr.Row():
120
-
121
- prompt = gr.Text(
122
- label="Prompt",
123
- show_label=False,
124
- max_lines=1,
125
- placeholder="Enter your prompt",
126
- container=False,
127
- )
128
-
129
- run_button = gr.Button("Run", scale=0)
130
-
131
- result = gr.Image(label="Result", show_label=False)
132
-
133
- with gr.Accordion("Advanced Settings", open=False):
134
-
135
- seed = gr.Slider(
136
- label="Seed",
137
- minimum=0,
138
- maximum=MAX_SEED,
139
- step=1,
140
- value=0,
141
- )
142
-
143
- randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
144
-
145
- with gr.Row():
146
-
147
- width = gr.Slider(
148
- label="Width",
149
- minimum=256,
150
- maximum=MAX_IMAGE_SIZE,
151
- step=32,
152
- value=1024,
153
- )
154
-
155
- height = gr.Slider(
156
- label="Height",
157
- minimum=256,
158
- maximum=MAX_IMAGE_SIZE,
159
- step=32,
160
- value=1024,
161
- )
162
-
163
- with gr.Row():
164
-
165
- guidance_scale = gr.Slider(
166
- label="Guidance Scale",
167
- minimum=1,
168
- maximum=15,
169
- step=0.1,
170
- value=3.5,
171
- )
172
-
173
- num_inference_steps = gr.Slider(
174
- label="Number of inference steps",
175
- minimum=1,
176
- maximum=50,
177
- step=1,
178
- value=28,
179
- )
180
-
181
- gr.Examples(
182
- examples = examples,
183
- fn = infer,
184
- inputs = [prompt],
185
- outputs = [result, seed],
186
- cache_examples="lazy"
187
- )
188
-
189
-
190
- gr.on(
191
- triggers=[run_button.click, prompt.submit],
192
- fn = infer,
193
- inputs = [prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
194
- outputs = [result, seed]
195
- )
196
-
197
- demo.launch()
198
-
199
-
200
-
 
 
 
110
  """
111
 
112
  with gr.Blocks(css=css) as demo:
113
+ with gr.Column(elem_id="col-container"):
114
+ gr.Markdown(f"""
115
+ Generate an image with Flux. Try it out and let me know what you think!
116
+ Expect roughly 45-60 seconds per generation with it's current backend.
117
+ This can be scaled up over time as needed. Thanks!
118
+ Not for Commercial Use - Apache 2.0 License
119
+ """)
120
+
121
+ with gr.Row():
122
+ prompt = gr.Text(
123
+ label="Prompt",
124
+ show_label=False,
125
+ max_lines=1,
126
+ placeholder="Enter your prompt",
127
+ container=False,
128
+ )
129
+
130
+ run_button = gr.Button("Run", scale=0)
131
+
132
+ result = gr.Image(label="Result", show_label=False)
133
+
134
+ with gr.Accordion("Advanced Settings", open=False):
135
+ seed = gr.Slider(
136
+ label="Seed",
137
+ minimum=0,
138
+ maximum=MAX_SEED,
139
+ step=1,
140
+ value=0,
141
+ )
142
+
143
+ randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
144
+
145
+ with gr.Row():
146
+ width = gr.Slider(
147
+ label="Width",
148
+ minimum=256,
149
+ maximum=MAX_IMAGE_SIZE,
150
+ step=32,
151
+ value=1024,
152
+ )
153
+
154
+ height = gr.Slider(
155
+ label="Height",
156
+ minimum=256,
157
+ maximum=MAX_IMAGE_SIZE,
158
+ step=32,
159
+ value=1024,
160
+ )
161
+
162
+ with gr.Row():
163
+ guidance_scale = gr.Slider(
164
+ label="Guidance Scale",
165
+ minimum=1,
166
+ maximum=15,
167
+ step=0.1,
168
+ value=3.5,
169
+ )
170
+
171
+ num_inference_steps = gr.Slider(
172
+ label="Number of inference steps",
173
+ minimum=1,
174
+ maximum=50,
175
+ step=1,
176
+ value=28,
177
+ )
178
+
179
+ gr.Examples(
180
+ examples=examples,
181
+ fn=infer,
182
+ inputs=[prompt],
183
+ outputs=[result, seed],
184
+ cache_examples="lazy",
185
+ )
186
+
187
+ gr.on(
188
+ triggers=[run_button.click, prompt.submit],
189
+ fn=infer,
190
+ inputs=[
191
+ prompt,
192
+ seed,
193
+ randomize_seed,
194
+ width,
195
+ height,
196
+ guidance_scale,
197
+ num_inference_steps,
198
+ ],
199
+ outputs=[result, seed],
200
+ )
201
+
202
+ demo.launch()