Upload folder using huggingface_hub
Browse files- .idea/workspace.xml +1 -1
- app.py +8 -1
.idea/workspace.xml
CHANGED
|
@@ -54,7 +54,7 @@
|
|
| 54 |
<option name="number" value="Default" />
|
| 55 |
<option name="presentableId" value="Default" />
|
| 56 |
<updated>1760056680813</updated>
|
| 57 |
-
<workItem from="1760056681869" duration="
|
| 58 |
</task>
|
| 59 |
<servers />
|
| 60 |
</component>
|
|
|
|
| 54 |
<option name="number" value="Default" />
|
| 55 |
<option name="presentableId" value="Default" />
|
| 56 |
<updated>1760056680813</updated>
|
| 57 |
+
<workItem from="1760056681869" duration="3537000" />
|
| 58 |
</task>
|
| 59 |
<servers />
|
| 60 |
</component>
|
app.py
CHANGED
|
@@ -50,12 +50,19 @@ def center_crop(image):
|
|
| 50 |
##### load model
|
| 51 |
config = "configs/pipelines/stage_2_base.py"
|
| 52 |
config = Config.fromfile(config)
|
| 53 |
-
model = BUILDER.build(config.model).
|
| 54 |
checkpoint_path = "checkpoints/Puffin-Base.pth"
|
| 55 |
checkpoint = torch.load(checkpoint_path, map_location='cpu')
|
| 56 |
_ = model.load_state_dict(checkpoint, strict=False)
|
| 57 |
_ = model.vae.load_state_dict(torch.load('checkpoints/vae.pth', map_location='cpu'), strict=True)
|
| 58 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 59 |
def fig_to_image(fig):
|
| 60 |
buf = io.BytesIO()
|
| 61 |
fig.savefig(buf, format='png', bbox_inches='tight', pad_inches=0)
|
|
|
|
| 50 |
##### load model
|
| 51 |
config = "configs/pipelines/stage_2_base.py"
|
| 52 |
config = Config.fromfile(config)
|
| 53 |
+
model = BUILDER.build(config.model).eval()
|
| 54 |
checkpoint_path = "checkpoints/Puffin-Base.pth"
|
| 55 |
checkpoint = torch.load(checkpoint_path, map_location='cpu')
|
| 56 |
_ = model.load_state_dict(checkpoint, strict=False)
|
| 57 |
_ = model.vae.load_state_dict(torch.load('checkpoints/vae.pth', map_location='cpu'), strict=True)
|
| 58 |
|
| 59 |
+
|
| 60 |
+
if torch.cuda.is_available():
|
| 61 |
+
harmon_model = model.to(torch.bfloat16).cuda()
|
| 62 |
+
else:
|
| 63 |
+
harmon_model = model.to(torch.float32)
|
| 64 |
+
|
| 65 |
+
|
| 66 |
def fig_to_image(fig):
|
| 67 |
buf = io.BytesIO()
|
| 68 |
fig.savefig(buf, format='png', bbox_inches='tight', pad_inches=0)
|