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Haresh-16/Public-Grievance-Detection-using-Resnet50-aided-by-GRADCAM
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1. pip install requirements.txt 2. Run FlaskAppv2.py in cmd 3. Hit "http://127:0.0.1:5000/dakshHit" in PostMan with Headers (key=Content-Type , value=multipart/form-data) and Body(key=image , value = (Files --> Image selected from 'Test images' in current dir) 4. Output description: defaultdict with two key-value pairs is outputted key- Ranking in order of precedence of correctness of alloted category value - list with [category_name , bounding_box_coordinates, confidence_%] category_name = Any one of (open manhole , overflowing garbage , patchy roads , proper road , proper bins , proper manholes) bounding_box_coordinates, = A rectangle highlighting the problem confidence_% = Confidence about correctness of output Example output: { "1": [ [ "open manhole", [ 0, 140, 496, 219 ], "99.97088313102722% Confidence" ] ], "2": [ [ "proper manhole", [ 209, 138, 280, 183 ], "0.02701951307244599% Confidence" ] ] }
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