Tophness2022 commited on
Commit
18cf7bd
·
1 Parent(s): 5adda77

improve styling

Browse files
Files changed (1) hide show
  1. gradio_server.py +26 -7
gradio_server.py CHANGED
@@ -24,7 +24,7 @@ import asyncio
24
  from wan.utils import prompt_parser
25
  PROMPT_VARS_MAX = 10
26
 
27
- target_mmgp_version = "3.3.0"
28
  from importlib.metadata import version
29
  mmgp_version = version("mmgp")
30
  if mmgp_version != target_mmgp_version:
@@ -39,6 +39,17 @@ tracker_lock = threading.Lock()
39
  file_list = []
40
  last_model_type = None
41
 
 
 
 
 
 
 
 
 
 
 
 
42
  def runner():
43
  global current_task_id
44
  while True:
@@ -57,7 +68,7 @@ def runner():
57
  item.update({
58
  'progress': f"{((current_step/total_steps)*100 if total_steps > 0 else 0):.1f}%",
59
  'steps': f"{current_step}/{total_steps}",
60
- 'time': f"{elapsed:.1f}s",
61
  'repeats': f"{repeats}",
62
  'status': f"{status}"
63
  })
@@ -213,14 +224,16 @@ def update_queue_data():
213
  with lock:
214
  data = []
215
  for item in queue:
 
 
 
216
  data.append([
217
- str(item['id']),
218
  item.get('status', "Starting"),
219
  item.get('repeats', "0/0"),
220
  item.get('progress', "0.0%"),
221
  item.get('steps', ''),
222
  item.get('time', '--'),
223
- (item['prompt'][:47] + '...') if len(item['prompt']) > 50 else item['prompt'],
224
  "↑",
225
  "↓",
226
  "✖"
@@ -2037,10 +2050,10 @@ def generate_video_tab(image2video=False):
2037
  , columns=[3], rows=[1], object_fit="contain", height=450, selected_index=0, interactive= False)
2038
  generate_btn = gr.Button("Generate")
2039
  queue_df = gr.DataFrame(
2040
- headers=["ID", "Status", "Repeats", "Progress", "Steps", "Time", "Prompt", "", "", ""],
2041
- datatype=["str", "str", "str", "str", "str", "str", "str", "str", "str", "str"],
2042
  interactive=False,
2043
- col_count=(10, "fixed"),
2044
  wrap=True,
2045
  value=update_queue_data,
2046
  every=1,
@@ -2390,6 +2403,12 @@ def create_demo():
2390
  overflow: hidden;
2391
  text-overflow: ellipsis;
2392
  }
 
 
 
 
 
 
2393
  #queue_df td:nth-child(7),
2394
  #queue_df td:nth-child(8),
2395
  #queue_df td:nth-child(9) {
 
24
  from wan.utils import prompt_parser
25
  PROMPT_VARS_MAX = 10
26
 
27
+ target_mmgp_version = "3.3.1"
28
  from importlib.metadata import version
29
  mmgp_version = version("mmgp")
30
  if mmgp_version != target_mmgp_version:
 
39
  file_list = []
40
  last_model_type = None
41
 
42
+ def format_time(seconds):
43
+ if seconds < 60:
44
+ return f"{seconds:.1f}s"
45
+ elif seconds < 3600:
46
+ minutes = seconds / 60
47
+ return f"{minutes:.1f}m"
48
+ else:
49
+ hours = int(seconds // 3600)
50
+ minutes = int((seconds % 3600) // 60)
51
+ return f"{hours}h {minutes}m"
52
+
53
  def runner():
54
  global current_task_id
55
  while True:
 
68
  item.update({
69
  'progress': f"{((current_step/total_steps)*100 if total_steps > 0 else 0):.1f}%",
70
  'steps': f"{current_step}/{total_steps}",
71
+ 'time': format_time(elapsed),
72
  'repeats': f"{repeats}",
73
  'status': f"{status}"
74
  })
 
224
  with lock:
225
  data = []
226
  for item in queue:
227
+ truncated_prompt = (item['prompt'][:97] + '...') if len(item['prompt']) > 100 else item['prompt']
228
+ full_prompt = item['prompt'].replace('"', '&quot;')
229
+ prompt_cell = f'<span title="{full_prompt}">{truncated_prompt}</span>'
230
  data.append([
 
231
  item.get('status', "Starting"),
232
  item.get('repeats', "0/0"),
233
  item.get('progress', "0.0%"),
234
  item.get('steps', ''),
235
  item.get('time', '--'),
236
+ prompt_cell,
237
  "↑",
238
  "↓",
239
  "✖"
 
2050
  , columns=[3], rows=[1], object_fit="contain", height=450, selected_index=0, interactive= False)
2051
  generate_btn = gr.Button("Generate")
2052
  queue_df = gr.DataFrame(
2053
+ headers=["Status", "Completed", "Progress", "Steps", "Time", "Prompt", "", "", ""],
2054
+ datatype=["str", "str", "str", "str", "str", "markdown", "str", "str", "str"],
2055
  interactive=False,
2056
+ col_count=(9, "fixed"),
2057
  wrap=True,
2058
  value=update_queue_data,
2059
  every=1,
 
2403
  overflow: hidden;
2404
  text-overflow: ellipsis;
2405
  }
2406
+ #queue_df td:nth-child(1) {
2407
+ width: 100px;
2408
+ }
2409
+ #queue_df td:nth-child(6) {
2410
+ width: 300px;
2411
+ }
2412
  #queue_df td:nth-child(7),
2413
  #queue_df td:nth-child(8),
2414
  #queue_df td:nth-child(9) {