Project dependencies may have API risk issues

[PyDeps]

Hi, In mlsd, inappropriate dependency versioning constraints can cause risks.

Below are the dependencies and version constraints that the project is using

numpy
opencv-python
pillow
tensorflow-gpu=2.3.0
Flask
gradio

The version constraint == will introduce the risk of dependency conflicts because the scope of dependencies is too strict.
The version constraint No Upper Bound and * will introduce the risk of the missing API Error because the latest version of the dependencies may remove some APIs.

After further analysis, in this project,
The version constraint of dependency numpy can be changed to >=1.8.0,<=1.23.0rc3.
The version constraint of dependency pillow can be changed to ==9.2.0.
The version constraint of dependency pillow can be changed to >=2.0.0,<=9.1.1.
The version constraint of dependency gradio can be changed to >=1.0.0a1,<=1.0.0a4.
The version constraint of dependency gradio can be changed to >=1.3.0,<=2.3.0a0.
The version constraint of dependency gradio can be changed to >=2.3.0,<=2.7.0a102.
The version constraint of dependency gradio can be changed to >=2.7.0,<=2.8.14.
The version constraint of dependency gradio can be changed to >=2.9.0,<=2.9.4.

The above modification suggestions can reduce the dependency conflicts as much as possible,
and introduce the latest version as much as possible without calling Error in the projects.

The invocation of the current project includes all the following methods.

The calling methods from the numpy

numpy.linalg.norm

The calling methods from the pillow

PIL.Image.open

The calling methods from the gradio

gradio.inputs.Number
gradio.Interface.launch

The calling methods from the all methods

absl.flags.DEFINE_integer
self.decoder2
tensorflow.keras.applications.mobilenet_v2.preprocess_input
square_list.np.array.reshape
Conv_BN_Act
flask.send_from_directory
inter_y.inter_x.np.concatenate.astype
stem_layer.get_weights
cv2.imdecode
cfg.cfg.dilate.cfg.topk.cfg.map_size.x.shape.Decoder
val1.numpy
self.load_tflite
self.get_pts_scores
tensorflow.keras.regularizers.l2
str
self.decoder1
tensorflow.lite.Interpreter.allocate_tensors
numpy.abs
gradio.inputs.Number
new_hough.current_hough.all
tensorflow.cast
absl.flags.DEFINE_string
tensorflow.keras.initializers.Constant
self.Conv_BN_Act.super.__init__
tensorflow.image.resize
tensorflow.lite.TFLiteConverter.from_keras_model
junc_list.append
numpy.frombuffer
tensorflow.lite.Interpreter.get_output_details
gradio.Interface.launch
interpreter.set_tensor
f.write
yx.numpy.numpy
range
tensorflow.keras.initializers.he_normal
len
numpy.transpose
numpy.argsort
block_name.block_dict.append
preprocess
layer_list
tensorflow.keras.applications.mobilenet_v2.MobileNetV2
PIL.Image.open
response.content.BytesIO.Image.open.convert
utils.pred_squares
flask.Flask.route
self.conv_block3
add_block_list.append
front_list.append
numpy.sum
argparse.ArgumentParser
uuid.uuid1
tensorflow.train.Checkpoint
urllib.request.urlretrieve
layer
self.final_act
tensorflow.lite.Interpreter
square_list.append
cv2.circle
tensorflow.train.CheckpointManager
init_worker
img_input.copy
flask.render_template
tensorflow.reshape
numpy.ones
cv2.line
self.conv_block4
numpy.sqrt
self.up_blocks.append
model_graph.decode_image
cv2.imwrite
flask.json.dump
numpy.unique
self.decoder0
Decoder_FPN
time.time
self.get_pts_scores_fast
absl.app.run
int
backbone_type.lower
argparse.ArgumentParser.add_argument
model
tensorflow.zeros
checkpoint.step.numpy
super.call
connect_list.append
numpy.array.append
tensorflow.concat
org_times.append
resized_image.np.expand_dims.astype
tensorflow.math.top_k
segment_list.append
self.BatchNormalization.super.__init__
_regularizer
flask.Flask.run
backbone_outputs.append
cfg.backbone_type.lower
model_graph.pred_tflite
numpy.max
tensorflow.expand_dims
numpy.expand_dims
numpy.mean
numpy.concatenate
tensorflow.where
model_graph.save_output
tensorflow.math.sigmoid
flask.request.files.save
argparse.ArgumentParser.parse_args
numpy.reshape
tensorflow.lite.TFLiteConverter.from_keras_model.convert
layer_name.split
cv2.polylines
cfg.x.Decoder_FPN
tensorflow.keras.layers.MaxPool2D
numpy.argmax
image.copy.copy
cv2.resize
gradio.Interface
square_length.append
tensorflow.gather_nd
BatchNormalization
tensorflow.math.equal
absl.flags.DEFINE_float
utils.pred_lines
cfg.post_name.backbone_type.Backbone
square.reshape
idx.self.up_blocks
check_outside_inside
top_layer
tensorflow.logical_and
lower
tensorflow.__version__.split
post_name.backbone_type.output_layers.extractor.input.Model
model_graph
numpy.roll
interpreter.get_tensor
os.path.join
os.makedirs
NotImplementedError
numpy.asarray
val2.numpy
open
self.conv_block2
interpreter.invoke
print
self.init_resize_image
tensorflow.train.Checkpoint.restore
end_list.append
modules.models.WireFrameModel
os.path.exists
self.Decoder.super.__init__
tensorflow.io.gfile.GFile
block_list.append
numpy.linalg.norm
logger.info
numpy.arctan2
format
requests.get
segments_list.append
absl.flags.DEFINE_boolean
tqdm.tqdm
Decoder
self.Upblock.super.__init__
self.conv
zip
flask.Flask
tensorflow.Variable
numpy.random.rand
tensorflow.ones
topk_values.numpy.numpy
tensorflow.keras.Model.summary
self.conv_block1
enumerate
self.Decoder_FPN.super.__init__
indices.hough.astype
Upblock
numpy.zeros
super
numpy.array
self.act_fn
segment_list.np.array.reshape
tensorflow.keras.layers.Input
numpy.sort
alpha_times.append
tensorflow.lite.Interpreter.get_input_details
merged_segments.append
tensorflow.constant
tensorflow.keras.layers.Conv2D
model_graph.read_image
segments_list.np.array.reshape
corner_info.corner_dict.append
numpy.arccos
model.read_image.copy
io.BytesIO
tensorflow.keras.layers.ReLU
new_model
io.BytesIO.getvalue
self.draw_output
self.bn
tensorflow.keras.Model
Backbone

@developer
Could please help me check this issue?
May I pull a request to fix it?
Thank you very much.