Built file with multitarget

app.py

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+__all__ = ['learn', 'classify_image', 'bear', 'env', 'age', 'image', 'label', 'examples', 'intf', 
+           'bear_err', 'bear_loss', 'environ_err', 'environ_loss', 'age_err', 'age_loss', 'combine_loss', 
+           'get_bear', 'get_age', 'get_environ']
+
+from fastai.vision.all import *
+import gradio as gr
+
+def get_bear(p): 
+    name_components = str(p).split(' ')
+    return name_components[2]
+
+def get_age(p):
+    name_components = str(p).split(' ')
+    return name_components[1]   
+
+def get_environ(p):
+    name_components = str(p).split(' ')
+    file_components = name_components[0].split('/')
+    return file_components[-1]
+
+def bear_err(inp,bear,environ,age): return error_rate(inp[:,:5],bear)
+def bear_loss(inp,bear,environ,age): return F.cross_entropy(inp[:,:5],bear)
+def environ_err(inp,bear,environ,age): return error_rate(inp[:,5:8],environ)
+def environ_loss(inp,bear,environ,age): return F.cross_entropy(inp[:,5:8],environ)
+def age_err(inp,bear,environ,age): return error_rate(inp[:,8:],age)
+def age_loss(inp,bear,environ,age): return F.cross_entropy(inp[:,8:],age)
+
+def combine_loss(inp,bear,environ,age):    
+    return bear_loss(inp,bear,environ,age)+environ_loss(inp,bear,environ,age)+age_loss(inp,bear,environ,age)
+
+learn = load_learner('multitarget_bears.pkl')
+
+bear = ('black', 'brown', 'grizzly', 'sloth', 'sun')
+env = ('forest', 'plains', 'water')
+age = ('adult', 'baby')
+
+def classify_image(img_path):
+    tst_dl = learn.dls.test_dl([img_path])
+    preds, _ = learn.get_preds(dl=tst_dl)
+    
+    idxs_bear = preds[:,:len(bear)].argmax(dim=1)
+    results_bear = pd.Series(bear[idxs_bear], name="idxs_bear")
+    
+    idxs_env = preds[:,len(bear):(len(bear)+len(env))].argmax(dim=1)
+    results_env = pd.Series(env[idxs_env], name="idxs_env")
+    
+    idxs_age = preds[:,(len(bear)+len(env)):(len(bear)+len(env)+len(age))].argmax(dim=1)
+    results_age = pd.Series(age[idxs_age], name="idxs_age")
+    
+    results = pd.DataFrame()
+    results['Bear'] = results_bear
+    results['Environment'] = results_env
+    results['Age'] = results_age
+    
+    return results
+
+image = gr.Image(height=192, width=192)
+outputs = gr.Dataframe()
+
+examples = ['Ronan_Grizzly_Bear_1.jpg', 'blackbear.jpg', 'blackbear2.jpg', 'brownbear.jpg', 'polar.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=outputs, examples=examples)
+intf.launch(inline=False)