prithivMLmods commited on
Commit
02f2ce5
·
verified ·
1 Parent(s): c4efb00

update app

Browse files
Files changed (1) hide show
  1. app.py +2 -12
app.py CHANGED
@@ -114,8 +114,6 @@ pipe_small_decoder.enable_model_cpu_offload()
114
  pipe_lock_standard = threading.Lock()
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  pipe_lock_small = threading.Lock()
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117
-
118
- # ── dimension helper ────────────────────────────────────────────────────────
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  def calc_dimensions(pil_img: Image.Image):
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  """
121
  Given a PIL image return (width, height) snapped to multiples of 8,
@@ -157,8 +155,6 @@ def update_dimensions_from_image(image_list):
157
 
158
  return calc_dimensions(img)
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160
-
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- # ── image parser ─────────────────────────────────────────────────────────────
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  def parse_and_resize_images(input_images, width: int, height: int):
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  """
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  Parse the gallery input and resize every frame to (width, height).
@@ -190,23 +186,18 @@ def parse_and_resize_images(input_images, width: int, height: int):
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  if not raw_list:
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  return None
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- # ── KEY FIX: resize every image to the exact pipeline dimensions ──
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  resized = [
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  img.resize((width, height), Image.LANCZOS)
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  for img in raw_list
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  ]
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  return resized
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200
-
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- # ── pipeline runner ───────────────────────────────────────────────────────────
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  def run_pipeline(pipe, lock, kwargs, seed):
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  with lock:
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  gen = torch.Generator(device="cpu").manual_seed(seed)
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  result = pipe(**kwargs, generator=gen).images[0]
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  return result
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208
-
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- # ── main inference ────────────────────────────────────────────────────────────
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  @spaces.GPU(duration=120)
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  def infer(
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  prompt,
@@ -265,7 +256,7 @@ def infer(
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  if image_list is not None:
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  shared_kwargs["image"] = image_list
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- progress(0.05, desc="Launching both pipelines simultaneously...")
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  with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor:
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  future_std = executor.submit(
@@ -279,7 +270,7 @@ def infer(
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  return_when=concurrent.futures.ALL_COMPLETED,
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  )
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- progress(0.95, desc="✅ Both pipelines done!")
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284
  out_standard = future_std.result()
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  out_small = future_small.result()
@@ -379,7 +370,6 @@ with gr.Blocks() as demo:
379
 
380
  run_button = gr.Button("Run Comparison", variant="primary")
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382
- # ── RIGHT COLUMN: outputs ───────────────────────────────────────
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  with gr.Column():
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  with gr.Row():
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  with gr.Column():
 
114
  pipe_lock_standard = threading.Lock()
115
  pipe_lock_small = threading.Lock()
116
 
 
 
117
  def calc_dimensions(pil_img: Image.Image):
118
  """
119
  Given a PIL image return (width, height) snapped to multiples of 8,
 
155
 
156
  return calc_dimensions(img)
157
 
 
 
158
  def parse_and_resize_images(input_images, width: int, height: int):
159
  """
160
  Parse the gallery input and resize every frame to (width, height).
 
186
  if not raw_list:
187
  return None
188
 
 
189
  resized = [
190
  img.resize((width, height), Image.LANCZOS)
191
  for img in raw_list
192
  ]
193
  return resized
194
 
 
 
195
  def run_pipeline(pipe, lock, kwargs, seed):
196
  with lock:
197
  gen = torch.Generator(device="cpu").manual_seed(seed)
198
  result = pipe(**kwargs, generator=gen).images[0]
199
  return result
200
 
 
 
201
  @spaces.GPU(duration=120)
202
  def infer(
203
  prompt,
 
256
  if image_list is not None:
257
  shared_kwargs["image"] = image_list
258
 
259
+ progress(0.30, desc="Launching both pipelines simultaneously...")
260
 
261
  with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor:
262
  future_std = executor.submit(
 
270
  return_when=concurrent.futures.ALL_COMPLETED,
271
  )
272
 
273
+ progress(0.80, desc="✅ Both pipelines done!")
274
 
275
  out_standard = future_std.result()
276
  out_small = future_small.result()
 
370
 
371
  run_button = gr.Button("Run Comparison", variant="primary")
372
 
 
373
  with gr.Column():
374
  with gr.Row():
375
  with gr.Column():