dfdfd

app.py

@@ -57,26 +57,33 @@ def predict_image(name_image):
     # path_in_repo="README.md",
     # repo_id="username/test-dataset",
     # repo_type="dataset",
+# 
+	# from huggingface_hub import HfApi
+	# api = HfApi()
+	# api.upload_file(
+    # 	path_or_fileobj="./" + name_image,
+    # 	path_in_repo=name_image,
+    # 	repo_id="valencar/modelo_raios_x",
+    # 	repo_type="dataset",
+	# 	)
 
-	from huggingface_hub import HfApi
-	api = HfApi()
-	api.upload_file(
-    	path_or_fileobj="./" + name_image,
-    	path_in_repo=name_image,
-    	repo_id="valencar/modelo_raios_x",
-    	repo_type="dataset",
-		)
 
 	fname =  path.abspath(path.join(path.dirname(__file__), name_image))
-	st.write(fname)
 
-	img = img_orig = image.load_img(fname, target_size = (IMAGE_HEIGHT, IMAGE_WIDTH))
+
+	import sys
+	from pathlib import Path
+	path_file = Path(sys.path[0])
+	print(path_file)
+	col1.header(path_file)
+
+	img = img_orig = image.load_img(path_file + '/' + name_image, target_size = (IMAGE_HEIGHT, IMAGE_WIDTH))
 	img = image.img_to_array(img)
 	img = np.expand_dims(img, axis = 0)
 	img = img/255.0
   
 
-	col1.image(fname, width=450)
+	col1.image(path_file + '/' + name_image, width=450)
 
 	pred = st.session_state.model.predict(img)
 	classe = np.argmax(pred)