SkalskiP commited on
Commit
bb81176
·
1 Parent(s): 7189c81
Files changed (1) hide show
  1. app.py +21 -15
app.py CHANGED
@@ -94,6 +94,7 @@ def process(
94
  image = image.resize((width, height), Image.LANCZOS)
95
 
96
  if segmentation_prompt_text:
 
97
  _, result = run_florence_inference(
98
  model=FLORENCE_MODEL,
99
  processor=FLORENCE_PROCESSOR,
@@ -107,7 +108,10 @@ def process(
107
  result=result,
108
  resolution_wh=image.size
109
  )
 
 
110
  detections = run_sam_inference(SAM_IMAGE_MODEL, image, detections)
 
111
 
112
  if len(detections) == 0:
113
  gr.Info(f"{segmentation_prompt_text} prompt did not return any detections.")
@@ -118,21 +122,23 @@ def process(
118
  mask = mask.resize((width, height), Image.LANCZOS)
119
  mask = mask.filter(ImageFilter.GaussianBlur(radius=10))
120
 
121
- if randomize_seed_checkbox:
122
- seed_slicer = random.randint(0, MAX_SEED)
123
- generator = torch.Generator().manual_seed(seed_slicer)
124
- result = FLUX_INPAINTING_PIPELINE(
125
- prompt=inpainting_prompt_text,
126
- image=image,
127
- mask_image=mask,
128
- width=width,
129
- height=height,
130
- strength=strength_slider,
131
- generator=generator,
132
- num_inference_steps=num_inference_steps_slider
133
- ).images[0]
134
- print('INFERENCE DONE')
135
- return result, mask
 
 
136
 
137
 
138
  with gr.Blocks() as demo:
 
94
  image = image.resize((width, height), Image.LANCZOS)
95
 
96
  if segmentation_prompt_text:
97
+ print('FLORENCE INFERENCE STARTED')
98
  _, result = run_florence_inference(
99
  model=FLORENCE_MODEL,
100
  processor=FLORENCE_PROCESSOR,
 
108
  result=result,
109
  resolution_wh=image.size
110
  )
111
+ print('FLORENCE INFERENCE DONE')
112
+ print('SAM INFERENCE STARTED')
113
  detections = run_sam_inference(SAM_IMAGE_MODEL, image, detections)
114
+ print('SAM INFERENCE DONE')
115
 
116
  if len(detections) == 0:
117
  gr.Info(f"{segmentation_prompt_text} prompt did not return any detections.")
 
122
  mask = mask.resize((width, height), Image.LANCZOS)
123
  mask = mask.filter(ImageFilter.GaussianBlur(radius=10))
124
 
125
+ return image, mask
126
+
127
+ # if randomize_seed_checkbox:
128
+ # seed_slicer = random.randint(0, MAX_SEED)
129
+ # generator = torch.Generator().manual_seed(seed_slicer)
130
+ # result = FLUX_INPAINTING_PIPELINE(
131
+ # prompt=inpainting_prompt_text,
132
+ # image=image,
133
+ # mask_image=mask,
134
+ # width=width,
135
+ # height=height,
136
+ # strength=strength_slider,
137
+ # generator=generator,
138
+ # num_inference_steps=num_inference_steps_slider
139
+ # ).images[0]
140
+ # print('INFERENCE DONE')
141
+ # return result, mask
142
 
143
 
144
  with gr.Blocks() as demo: