session_hash
Browse files- .gitignore +2 -1
- app.py +6 -5
.gitignore
CHANGED
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@@ -1 +1,2 @@
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-
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+
*.egg-info/
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+
__pycache__/
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app.py
CHANGED
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@@ -16,6 +16,7 @@ import tempfile
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import cv2
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import matplotlib.pyplot as plt
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import numpy as np
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import spaces
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import torch
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@@ -97,7 +98,7 @@ def reset(
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session_input_labels,
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request: gr.Request,
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):
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-
session_id = request.
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predictor.to("cpu")
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session_input_points = []
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session_input_labels = []
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@@ -125,7 +126,7 @@ def clear_points(
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session_input_labels,
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request: gr.Request,
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):
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session_id = request.
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predictor.to("cpu")
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session_input_points = []
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session_input_labels = []
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@@ -148,7 +149,7 @@ def preprocess_video_in(
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session_input_labels,
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request: gr.Request,
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):
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-
session_id = request.
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predictor.to("cpu")
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if video_path is None:
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return (
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@@ -225,7 +226,7 @@ def segment_with_points(
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evt: gr.SelectData,
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request: gr.Request,
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):
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session_id = request.
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if torch.cuda.get_device_properties(0).major >= 8:
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torch.backends.cuda.matmul.allow_tf32 = True
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torch.backends.cudnn.allow_tf32 = True
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@@ -308,7 +309,7 @@ def propagate_to_all(
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session_all_frames,
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request: gr.Request,
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):
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session_id = request.
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predictor.to("cuda")
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if torch.cuda.get_device_properties(0).major >= 8:
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torch.backends.cuda.matmul.allow_tf32 = True
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import cv2
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import matplotlib.pyplot as plt
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import numpy as np
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+
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import spaces
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import torch
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session_input_labels,
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request: gr.Request,
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):
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+
session_id = request.session_hash
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predictor.to("cpu")
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session_input_points = []
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session_input_labels = []
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session_input_labels,
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request: gr.Request,
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):
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+
session_id = request.session_hash
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predictor.to("cpu")
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session_input_points = []
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session_input_labels = []
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session_input_labels,
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request: gr.Request,
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):
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+
session_id = request.session_hash
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predictor.to("cpu")
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if video_path is None:
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return (
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evt: gr.SelectData,
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request: gr.Request,
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):
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session_id = request.session_hash
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if torch.cuda.get_device_properties(0).major >= 8:
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torch.backends.cuda.matmul.allow_tf32 = True
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torch.backends.cudnn.allow_tf32 = True
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session_all_frames,
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request: gr.Request,
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):
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+
session_id = request.session_hash
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predictor.to("cuda")
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if torch.cuda.get_device_properties(0).major >= 8:
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torch.backends.cuda.matmul.allow_tf32 = True
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