Spaces:
Running
on
Zero
Running
on
Zero
claude2.7
Browse files
app.py
CHANGED
@@ -3,6 +3,7 @@ import spaces
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import os
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import shutil
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os.environ['TOKENIZERS_PARALLELISM'] = 'true'
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os.environ['SPCONV_ALGO'] = 'native'
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from typing import *
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@@ -18,6 +19,14 @@ import traceback
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import sys
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MAX_SEED = np.iinfo(np.int32).max
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TMP_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'tmp')
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os.makedirs(TMP_DIR, exist_ok=True)
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@@ -123,9 +132,14 @@ def text_to_3d(
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video = [np.concatenate([video[i], video_geo[i]], axis=1) for i in range(len(video))]
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video_path = os.path.join(user_dir, 'sample.mp4')
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imageio.mimsave(video_path, video, fps=15)
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state = pack_state(outputs['gaussian'][0], outputs['mesh'][0])
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torch.cuda.empty_cache()
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-
return
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@spaces.GPU(duration=90)
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import os
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import shutil
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import json
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os.environ['TOKENIZERS_PARALLELISM'] = 'true'
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os.environ['SPCONV_ALGO'] = 'native'
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from typing import *
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import sys
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# Add JSON encoder for NumPy arrays
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class NumpyEncoder(json.JSONEncoder):
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def default(self, obj):
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if isinstance(obj, np.ndarray):
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return obj.tolist()
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return json.JSONEncoder.default(self, obj)
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MAX_SEED = np.iinfo(np.int32).max
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TMP_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'tmp')
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os.makedirs(TMP_DIR, exist_ok=True)
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video = [np.concatenate([video[i], video_geo[i]], axis=1) for i in range(len(video))]
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video_path = os.path.join(user_dir, 'sample.mp4')
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imageio.mimsave(video_path, video, fps=15)
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# Create the state object and ensure it's JSON serializable for API calls
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state = pack_state(outputs['gaussian'][0], outputs['mesh'][0])
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# Convert to serializable format
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serializable_state = json.loads(json.dumps(state, cls=NumpyEncoder))
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torch.cuda.empty_cache()
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return serializable_state, video_path
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@spaces.GPU(duration=90)
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