how to run pretrained model? about csp HOT 6 OPEN

I've got the pretrained model from google drive,
but I now can't figure out how to actually run them.
What parts of codes should I modify , and what command lines should I use to run them?

Can you kindly share the Google Drive link to the pre-trained model.

https://drive.google.com/drive/folders/1Y1cGm-sRO0VMSHnDqfmIWA_hl-2fqPWn

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I've got the pretrained model from google drive,
but I now can't figure out how to actually run them.
What parts of codes should I modify , and what command lines should I use to run them?

hi, have you run the pretrained model?
Can you tell me how to run the pretrained model?

from csp.

I've got the pretrained model from google drive,
but I now can't figure out how to actually run them.
What parts of codes should I modify , and what command lines should I use to run them?

Can you kindly share the Google Drive link to the pre-trained model.

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From test_caltech.py, change some lines.

#if not os.path.exists(out_path):
#os.makedirs(out_path)
#files = sorted(os.listdir(w_path)) # get each files in w_path + sorting
#for w_ind in range(51, 121): # get files from epoch 51 to 120
#for f in files:
#if f.split('')[0] == 'net' and int(f.split('')[1][1:]) == w_ind: # if net epoch 51~120
#break
cur_file = 'net_e82_l0.00850005054218.hdf5' # pretrained from citypersons
weight1 = os.path.join(w_path, cur_file) # pathname + file name
print 'load weights from {}'.format(weight1)
model.load_weights(weight1, by_name=True) # get weight from trained models
res_path = os.path.join(out_path, '082+city') #result path = valresults/caltech/h/off/065 ###

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Also I have changed the score from 0.01 to 0.5 following #38
boxes = bbox_process.parse_det_offset(Y, C, score=0.5,down=4) # originally 0.01

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Also I have changed the score from 0.01 to 0.5 following #38
boxes = bbox_process.parse_det_offset(Y, C, score=0.5,down=4) # originally 0.01

Excuse me, I have made the codes work and tested my images. But the output of 'Y' is a tensor close to zero. Could you give me some advice? Thanks.
Y = model.predict(x_rcnn)

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